Explorez tous les épisodes du podcast Digital Pathology Podcast
| Titre | Date | Durée | |
|---|---|---|---|
| 170: Inside SITC 2025: How Multiplex IF Is Changing Cancer Care | 07 Nov 2025 | 00:22:50 | |
Can spatial biology and multiplex immunofluorescence truly transform how we understand cancer? I went live from the Society for Immunotherapy of Cancer (SITC) 2025 — the 40th Anniversary Meeting to explore how spatial biology, multiplex IF, and digital pathology are coming together to redefine cancer diagnostics, research, and precision medicine. This session kicked off a weekend of cutting-edge discussions with leaders from Hamamatsu (Booth 415) and Biocare Medical (Booth 717) — two companies helping laboratories around the world embrace digital transformation and spatial imaging in oncology. 🧠 Episode Highlights & Key Moments 0:00 — Introduction ~1:00 — What Is Multiplex Immunofluorescence (IF)? ~2:30 — The Spatial Biology Revolution ~5:00 — Digital Pathology & AI Readiness ~7:30 — Featured Booths at SITC 2025
~9:00 — Real-World Impact ~12:00 — Getting Started ~15:00 — Audience Q&A ~20:00 — Future Directions ~24:00 — Wrap-Up & Takeaways Resources Mentioned 🔹 Hamamatsu Photonics (Booth 415) 🔹 Biocare Medical (Booth 717) 🔹 SITC 2025 Official Information My Takeaway: Spatial biology and multiplex IF a | |||
| 169: AI Across Organ Systems: Kidney, Liver, Colon, Bladder, and Beyond | 03 Nov 2025 | 00:37:50 | |
Can one AI system learn from every organ — and teach us something new about all of them? In this edition of DigiPath Digest #31, I explore how artificial intelligence is transforming pathology across multiple organ systems, revealing connections that help us diagnose faster, more consistently, and more accurately than ever before. From glomerulonephritis to hepatocellular carcinoma, AI is no longer confined to a single specialty — it’s becoming the connective tissue between them. What’s Inside: 1️⃣ AI for Bladder Cancer Classification 2️⃣ AI in Colorectal Cancer Care 3️⃣ AI for Glomerular Nephritis Diagnosis 4️⃣ AI in Liver Disease (MASLD & HCC) 5️⃣ Lightweight AI for Domain Generalization My Takeaway Across every study, a single message stands out: Episode Highlights
Join me next time for updates from the SITC 2025 Conference, where I’ll be live at Booth 415 with Hamamatsu and Biocare, discussing how AI and spatial biology are converging to drive clinical utility. #DigitalPathology #AIinHealthcare #ComputationalPathology #CancerDiagnostics #LiverPathology #RenalPathology #FutureOfMedicine #DigiPathDigest | |||
| 160: AI in Medicine: Neuropathology, Renal Disease, Hematology & Cytology | 31 Aug 2025 | 00:25:14 | |
What if the way we quantify pathology is more guesswork than science? In this episode of DigiPath Digest, I take you through the latest research where AI is not just supporting but challenging traditional methods of image analysis in neuropathology, nephrology, hematology, and cytology. From Boston brain banks to Mayo Clinic kidney models, we look at how advanced AI compares to human vision—and where it already outperforms us. Episode Highlights:
Resources from this Episode
| |||
| 70: Digital Pathology 101 Chapter 1 (Part 1) | Digital Pathology Milestones and Basic Digitalization Concepts | 10 Oct 2023 | 00:51:11 | |
Get the PDF of "Digital Pathology 101" Book here Get the paper copy of "Digital Pathology 101" on AMAZON
This book is the culmination of months of passion and hard work. If you've been following me on social media, you know it's been a labor of love. But why did I write this book, you might ask? Well, it's your comprehensive guide to navigating and thriving in the realm of digital pathology. But first, let's rewind a bit. Back in 2003, Dr. Anil Parwani predicted that everyone would be digital by 2007. Well, that might have been a bit too optimistic, but guess what? The digital age in pathology is here, and it's not a distant future; it's right around the corner. I'm convinced that now is the time, and that's why I'm so excited to share this book with you. But enough about that, let's dive into the first chapter of the audio version of "Digital Pathology 101." In this chapter, we'll explore the historical milestones that paved the way for digital pathology. So, without further ado, let's get started on this journey into the world of digital pathology. Here is what we will cover in this part of chapter 1:
BASIC DIGITALIZATION CONCEPTS
-------------------------------------------------------------------------------------- Get the PDF of "Digital Pathology 101" Book here | |||
| 69: How to Set Realistic Expectation in Digital Transformation w/ Anil Parwani, Ohio State University | 04 Oct 2023 | 00:33:46 | |
In this episode of "The Digital Pathology Podcast," we delve into the fascinating career of Dr. Anil Parwani from Ohio State University, a visionary whose ardor for technology and research paved the way for groundbreaking advancements in digital pathology.
DIGITAL PATHOLOGY RESOURCES: | |||
| 68: The Evolution of Digital Pathology: 2013 vs. 2023 w/ Dr. Matthew O. Leavitt, DDx Foundation | 20 Sep 2023 | 00:56:12 | |
What happened to digital pathology in the last decade?
| |||
| 67: What Is the Role of Digital Pathology in Clinical Trials w/ Monika Lamba Saini | 29 Aug 2023 | 00:29:00 | |
How is digital pathology used in clinical trials? Because digital pathology as a discipline began with the aim of streamlining clinical trials, one could assume that this is currently the default.
DIGITAL PATHOLOGY RESOURCES: | |||
| 66: What You Need to Know About Digital Pathology Trends: Takeaways from the DP & AI Global Engage Event with Giovanni Lujan | 02 Aug 2023 | 00:20:50 | |
Welcome to a very spontaneous and exciting episode of the Digital Pathology Podcast. In this episode, I had the pleasure of sitting down with Dr. Giovanni Lujan from Ohio State University, whom you might remember from our previous crossover podcasts with Beyond the Scope. Recently, we were at the Digital Pathology and AI Congress in New York organized by Global Engage, and guess what? We decided to record this episode right there, surrounded by the buzz of the conference. No fancy preparations, just real and raw insights for you. Giovanni and I are sharing our impressions and discussing the latest trends in digital pathology that were highlighted at the Congress. It's fantastic to finally meet in person after collaborating on two podcasts together. Giovanni has been a devoted follower of our podcast and all things digital pathology, and I'm truly inspired by his passion for the field. The Congress organized by Global Engage has a unique vibe. It's smaller, which allows for more meaningful interactions and networking opportunities with fellow professionals and vendors. The longer breaks and one-on-one meetings foster valuable connections, making this conference stand out from the rest.
DIGITAL PATHOLOGY RESOURCES:
Keywords: Digital Pathology Congress Recap, Networking, Insights, Global Engage Impact, Giovanni Lujan, Beyond the Scope, Cutting-edge Innovations, Stay Updated, Join Now | |||
| 65: What Is Translational Research In Digital Pathology? /w Anant Madabhushi, Emory University & Georgia Tech | 06 Jul 2023 | 00:51:03 | |
DIGITAL PATHOLOGY RESOURCES:
| |||
| 64: How To Overcome Challenges In Image Analysis For Spatial Biology w/ Lorenz Rognoni, Ultivue | 08 Jun 2023 | 00:20:56 | |
Get ready for a deep dive into spatial biology and image analysis with Lorenz Rognoni, the Director of Image Data Science at Ultivue. Ultivue is a company specializing in spatial biology and Lorenz brings his wealth of knowledge in multiplex immunofluorescence (mIF) and image data science to this great conversation.
We kick off our discussion by addressing the inherent challenges in multiplex IF. The conversation spans a range of issues including tissue preparation artifacts, unique tissue morphology, and antibody-specific staining. The vast variability of tissues, differing across body regions, species, and health conditions, is a recurring theme. We also delve into the effectiveness of expert visual evaluation for traditional stains and the need for new strategies to interpret high-dimensional data.
Shifting gears, we discuss the role of brightfield imaging in spatial biology. Is there still space for brightfield if we want to learn the spatial interactions of cells in the tissue? Is this method not too limiting?
Our conversation culminates in a look at the challenges and potential missteps in moving from image analysis to interpreting the data generated. Lorenz points out the crucial process of extracting meaningful insights from millions of cells, defining appropriate phenotypes, and considering the intricacies of downstream data mining.
Join us for this insightful conversation and gain a deeper understanding of the complexities and nuances of spatial biology and image data science with Lorenz Rognoni. Keywords: Lorenz Rognoni, Ultivue, spatial biology, image analysis, multiplex immunofluorescence, tissue morphology, brightfield imaging, data mining
DIGITAL PATHOLOGY PLACE RESOURCES: | |||
| 63: Is this the year of AI in pathology? And what about ChtGPT? A crossover podcast with Beyond the Scope. | 24 May 2023 | 00:33:39 | |
Welcome to the crossover podcast with David, Giovanni and myself (Aleks) again. During this episode, we explore the world of digital pathology, artificial intelligence, including Chat GPT, and their growing importance in the field. | |||
| 62: Changing Stereotypes of Pathology. How Pathologists Contribute to Patient Care w/ Marilyn Bui, Moffitt Cancer Center | 02 May 2023 | 00:36:04 | |
Have you heard the stereotype of a pathologist hidden behind the microscope (or in the era of digital pathology behind the computer screen). Pathologist as the doctors' doctor? In this episode, Dr. Bui shares her background and how she became a patient-centered pathologist. She talks about her work in tissue pathology, cytopathology, and digital pathology at Moffitt Cancer Center in Tampa, Florida, where she also teaches and conducts research. Join me in this conversation with Dr. Marilyn Bui as we delve deeper into the world of pathology and learn more about her book, "The Healing Art of Pathology."
----------------------------------------------------------------- | |||
| 61: The best online pathology book ever w/ Nat Pernick, PathologyOutlines.com | 17 Apr 2023 | 00:24:47 | |
Introduction About PathologyOutlines.com PathologyOutlines.com Peer Review Process Contributing to PathologyOutlines.com Personal Profile on PathologyOutlines.com IHC Stains and CD Markers Explained Digital Pathology Starter Kit Keywords: digital pathology, pathology professionals, PathologyOutlines.com, online pathology resource, peer review process, contributors, IHC stains, CD markers, digital pathology starter kit, personal profile.
| |||
| 159: What If Your AI Tool Is Lying: Hidden Bias in Pathology Algorithms | 30 Aug 2025 | 00:27:49 | |
What if the AI tools we trust for cancer diagnosis are not always correct? This episode of DigiPath Digest takes on the uncomfortable but critical question: can AI “lie” to us—and how do we verify its performance before adopting it in clinical practice? Highlights:
Resources from this Episode
| |||
| 60: End-to-End Solution for Digital Pathology w/ Leif Honda, TriMetis Life Sciences | 10 Apr 2023 | 00:48:46 | |
In digital pathology is it best to start small and incrementally implement the technology or go all in to reap all the the benefits at once? THIS EPISODE'S RESOURCES: | |||
| 59: Top 5 Mistakes you must AVOID in using Machine Learning for pathology w/ Heather Couture, PixelScientia Labs | 22 Mar 2023 | 00:32:20 | |
The field of pathology has been revolutionized by the introduction of machine learning techniques, which enable more efficient and accurate diagnoses and have the potential to some day even eliminate or reduce the number of expensive molecular tests. However, the model development is a complex process and there are certain mistakes that must be avoided when using machine learning for pathology.
| |||
| 58: The Regulatory Aspect of Digital Pathology and Translational Medicine w/ Esther Abels | 15 Mar 2023 | 00:33:36 | |
Today's podcast is about the regulatory aspect of digital pathology and how it fits into the space between research and clinical use called translational medicine. There are however regulatory requirements that need to be taken into consideration when developing and using digital pathology tools. For example tissue image analysis tools used to support clinical decisions need to adhere to the FDA's guidance for software as a medical device. The FDA is also working to define data sets that can be validated and reused for algorithm development. It is a best practice to engage with the FDA early and this process for drug and medical device companies starts with a pre-submission to the FDA, seeking advice and discussing the approach. To be successful the role of a regulatory architect is crucial in overseeing the process and guiding it from point A to B to Z.
| |||
| 57: Beyond innovation - how to embrace responsibility and leadership in digital pathology at a personal and national level w/ Inti Zlobec | 08 Mar 2023 | 00:34:33 | |
Today is the International Women's Day and this month at the Digital Pathology Podcast I decided to invite some incredible women who are leaders in the digital pathology field. Her background is in statistics and computational research combined with a PhD in experimental pathology at the University of McGill in Canada. Combining and hybridizing those two fields has been a blessing for her in bringing people with different backgrounds together. Bothe her background and personality make here a natural connector of all digital pathology links. Pathologists should not just be used for annotations and quick checks, but should be included in projects as equal contributors. This would be the first initiative of this kind at a national level which will create a fantastic model for others to tweak and follow. | |||
| 56: The beginnings of computational pathology w/ Jeroen van der Laak, Radboud UMC | 21 Feb 2023 | 00:25:40 | |
Computational pathology – how did this field even start? In today’s episode my guest is Jeroen van der Laak, computational pathology professor at Radboud University Medical Center, who was recently listed on "The Pathologist Power List" in the category “Strange New worlds” Jeroen has been in the field of computational pathology for over 30 years and has seen it being created and evolve. He witnessed how advancements in whole-slide imaging and deep learning have allowed for the practical application of AI in pathology. Throughout the evolution of the field of computational pathology the focus has shifted from research-oriented work to direct collaboration with clinicians to test AI in diagnostic practice. During his tenure Jeroen has seen what it takes to be successful in the field of computational and digital pathology. To be a successful researcher in this field you need to understand the importance of high quality data and understand how the field of pathology works and what you see in the tissue you are analyzing. This is a very collaborative field and a responsibility of an AI researcher is making AI accessible and breaking down technical aspects for pathologists. Jeroen co-leads the Computational Pathology Group at Radboud with two other researchers – Francesco Ciompi and Geert Litjens. Their criteria for choosing successful candidates for a digital pathology group include good team spirit, collaboration, willingness to learn, and understanding of the field. It is just a matter of (not too much) time when AI will become mainstream in pathology labs and will improve the accuracy and speed of patient diagnosis. Just like whole slide scanning is becoming part of the routine pathology workflow, so will AI based image analysis.
| |||
| 55: Merging hardware and software to deliver 2nd generation digital pathology w/ Prasanth Perugupalli, Pramana | 31 Jan 2023 | 00:36:08 | |
Although digital pathology was supposed to be faster and more seamless than classical pathology on glass there are still many manual steps in the workflow.
| |||
| 54: Cytomine - a free the tissue image analysis tool for all: pathologists, developers and the lab w/ Gregoire Vincke, Cytomine | 22 Jan 2023 | 00:50:55 | |
Do you want to do tissue image analysis for FREE? THIS EPISODE'S RESPOURCES: -------------------------------- | |||
| 53: Why digital pathology will be mainstream soon w/ Aleksandra Zuraw, Digital Pathology Place | 29 Dec 2022 | 00:08:29 | |
I started working in the digital pathology space, because it sounded cool. | |||
| 52: What does the FDA say about non-clinical digital pathology for GLP? | 20 Dec 2022 | 00:26:55 | |
Several scanners have been cleared by the FDA for clinical pathology work, but what about FDAs stand on all the nonclinical pathology work done in a regulatory environment? Specifically the work done in the Good Laboratory Practice (GLP) compliant environment?
Good news! This episode's resources: | |||
| 51: What should we fix in digital pathology with Puneet Pantane, Crosscope | 30 Nov 2022 | 00:26:27 | |
As much as I love Digital Pathology - things that are not always perfect, and the integrations of systems are not always seamless. We don't need to sugar coat it.
If you want to learn more about Crosscope, click here | |||
| 158: Multimodal Magic AI’s Role in Lung & Prostate Cancer Predictions | 29 Aug 2025 | 00:28:50 | |
What if AI could predict cancer outcomes better than traditional methods—and at a fraction of the cost? In this episode, I explore how multimodal AI is reshaping lung and prostate cancer predictions and why integration challenges still stand in the way. Episode Highlights with Timestamps:
Resources from this Episode
| |||
| 50: How to approach colon cancer with supervised deep learning image analysis w/ Rish Pai, Mayo Clinic | 21 Nov 2022 | 00:34:16 | |
This episode is brought to you by Aiforia. Thank you Aiforia :)
THIS EPISODE'S SPECIAL OFFER "THE BETA COHORT" | |||
| 49: Scaling up your digital pathology operations with Mark Zarella, Mayo Clinic | 08 Nov 2022 | 00:29:43 | |
This episode is brought to you by Hamamatsu. Thank you Hamamatsu :)
| |||
| 48: What the heck is DICOM in Pathology? w/ David Clunie, PixelMed Publishing | 28 Oct 2022 | 00:42:54 | |
As the digital pathology community is embarking on the journey of DICOM implementations questions we haven't asked ourselves arise...
Who would be a better guest to talk about it than the DICOM standard editor himself, Dr. David Clunie?
OTHER EPISODES YOU MIGHT LIKE: | |||
| 47: Artificial Intelligence in Digital Pathology (a conference talk recording) w/ Aleksandra Zuraw | 22 Oct 2022 | 00:28:52 | |
Join me for the FREE Independent Digital Pathology Event "Bridging the Gap Between Pathology and Computer Science" 👇 | |||
| 46: Leveraging the power of static telecytology for veterinary diagnostics w/ Kate Baker | 10 Oct 2022 | 00:51:03 | |
Did you know that pathology diagnostics through a smartphone is a thing?
| |||
| 45: What's up in Digital Pathology - a crossover podcast with Beyond the Scope | 16 Sep 2022 | 00:34:54 | |
This is a joint podcast episode where the hosts of "Beyond the Scope" - the official Digital Pathology Association podcast and the host of the "Digital Pathology Podcast" meet to talk about what is going on in our discipline. YouTube Version of THIS episode is here.
AUDIO: https://digitalpathologyplace.com/pod... VIDEO: https://www.youtube.com/watch?v=wECId... Podcasts with Chen Sagiv, DeePathology: Digital pathology Podcast: https://youtu.be/DrEUnkYkN28 Beyond the Scope: https://podcasts.apple.com/no/podcast... Podcasts with David Clunie, Pixelmed Publishing: Digital Pathology Podcast: https://digitalpathologyplace.com/pod... Beyond the Scope: https://podcasts.apple.com/us/podcast... Pathology Visions 2022 registration page: https://digitalpathologyassociation.o... | |||
| 44: Weakly supervised AI for pathology w/ Geert Litjens, RadboudUMC | 28 Jul 2022 | 00:53:19 | |
Have you ever wondered what semi-supervised, weekly, and unsupervised artificial intelligence digital pathology models can do to help pathologists?
Other podcast episodes you'll enjoy:
| |||
| 43: Never miss a piece of digital pathology knowledge ever again! Digital Pathology Place and Pathology News partnership w/ Jonathon Tunstall | 05 Jul 2022 | 00:21:36 | |
There are a few websites online other than the Digital Pathology Place that talk about different aspects of digital pathology. An important one being Pathology News.
| |||
| 42: BigPicture - the largest whole slide repository for AI model development in pathology. Where do we stand at month 15/72? | 17 Jun 2022 | 00:37:23 | |
Deep learning artificial intelligence has entered the field of digital pathology and is here to stay because it consistently outperforms the classical image analysis methods on pathology slides.
Listen to the full episode to learn all about it.
Episodes you might also like:
| |||
| 41: Digital Pathology for Dermatologists. How Pathology Watch managed to incorporate digital pathology in dermatology practices across the US w/ Dan Lambert, Pathology Watch | 25 Apr 2022 | 00:23:13 | |
Digital pathology is supposed to help pathologists provide better patient care and make their lives easier, but what about other doctors, do they even care? Maybe radiologists? Oncologists? Nope…Dermatologists! They do care! And they are the clients of Pathology Watch – a CLIA lab specializing in dermatopathology, that is currently servicing samples from over 65 dermatology clinics in the USA. Pathology Watch provides an end-to-end digital pathology solution for dermatologists. From processing the samples sent by the dermatologists, through the dermatopathology report to the whole slide image of the diagnosed sample, and all this browser-based and integrated with the dermatology clinic’s electronic medical record (EMR) systems. This provides a completely non-disruptive workflow. Pathology Watch is providing a true end-to-end solution built around dermatologists. The EMR integration saves the dermatologists time (25h/ month!!! Who would not want to have that?!?) and whole slide images build the bridge between and improve the communication on the “patient-dermatologist-pathologist” line. Dermatologists can show the images of the cases to the patients, and they can see the highlighted areas used by the pathologist when diagnosing the case. Once the digitization and intersystem integration take care of the time savings it’s time to step up the game! The next step is using artificial intelligence for better dermatopathology diagnostics and to gain even more time savings. Pathology Watch designed its AI pipeline specifically to bypass the known industry problem of generalizability of AI models. It is extremely difficult to train generalizable models on samples from different institutions, but if the samples are processed in just one lab in a very controlled environment, using automated equipment and performing rigorous quality control, the pre-analytical variability causing a lack of generalizability is taken care of. As in any digital pathology operation, troubleshooting is part of the business. What do you do when your scanner breaks down? How do you store the digital pathology images effectively in a cost-efficient way? And how do you deliver the slides in the browser FAST? It took the Pathology Watch team a few years to solve those and other challenges and come up with good mitigation strategies. Do you want to know how they did it? Listen to the full episode to learn more from Dan Lambert, the CEO of Pathology Watch.
This Episodes resources | |||
| 157: How Academic Pathology Programs Can Prepare for AI | UPMC Podcast | 22 Aug 2025 | 00:38:52 | |
“AI in Pathology Isn’t Coming — It’s Already Here. Are You Ready?” From confusion to clarity — that’s what this episode is all about. I sat down with Drs. Liron Pantanowitz, Hooman Rashidi, and Matthew Hanna to dissect one of the most important and comprehensive AI-in-pathology resources ever created: the 7-part Modern Pathology series from UPMC’s Computational Pathology & AI Center of Excellence (CPAiCE). This isn’t just another opinion piece — it's your complete guide to understanding, implementing, and navigating AI in pathology with real-world insights and a global lens. Together, we discuss:
If you’ve ever asked, “Where do I even start with AI in pathology?” — this is your answer.
📰 Read the full series (open access!): 👨⚕️ UPMC’s Computational Pathology & AI Center of Excellence (CPAiCE) | |||
| 40: A simple microscope camera, whole slide scanner and everything in between. The different tiers of digital pathology w/ Mike Miller, I. Miller Microscopes | 14 Apr 2022 | 00:33:55 | |
A common misconception about digital pathology is that it is synonymous with whole slide imaging and has a high price point. This is not the case, as one can enter the digital pathology world and benefit from what it has to offer with a simple microscope camera. If we would like a more sophisticated solution, but don't want to get a whole slide scanner or don't have the use case or business case to justify it, no worries, there is enough to choose from!
Listen to the full episode to learn the details and the price points of each solution!
Episodes you might also like: | |||
| 39: How image analysis and artificial intelligence support digital pathology-enabled precision medicine today and what to expect in the future w/ Michael Grunkin, Visiopharm | 15 Mar 2022 | 00:20:08 | |
This episode is brought to you by Visiopharm. One of the causes of the slow adoption is that going digital in a pathology lab means a much bigger investment than just the cost of the whole slide scanners for slide digitization. Additional costs include digital storage and infrastructure, slide and workflow management, and connectivity to lab information systems. Because the improvements in precision and productivity gained by going digital are modest at best, a higher value is expected from image analysis and artificial intelligence. The research and diagnostic applications of image analysis have been explored for decades already and many have found great use in the research-diagnostics continuum. However, a large need for the standardization of tissue diagnostic assays remains unmet. Standardization of the staining and of the diagnostic interpretation of tests would tremendously benefit pathology and patient care. So far, the standardization efforts focused on the interpretation part of the puzzle. Several quantification algorithms have been developed, many of which received regulatory clearance. At the same time, the IHC assays on which the algorithms are based often lack standardization, and this is where more effort should be put. Currently, only pathology institutions that go fully digital reap the digital pathology benefits. There is not an efficient way to start slowly, rather it seems to be “all or nothing”. Enabling institutions to embark on the digital pathology journey in an incremental fashion would change the digital pathology landscape and significantly increase the adoption of this technology. The more value on different fronts digital pathology can provide to institutions and patients, the more the adoption will increase. And we have not yet explored all the ways in which value can be provided. Listen to the full episode to learn about it in more detail and visit Visiopharm’s website, to learn how they are contributing to the digital transformation in pathology. | |||
| 38: From digital microscopy to digital pathology through image analysis. How far have we come in 20 years? w/ Michael Grunkin, Visiopharm | 08 Mar 2022 | 00:18:49 | |
Visiopharm is a company offering image analysis software used on pathology images. The software has been on the market for over 20 years and has evolved through the transition of digital microscopy to digital pathology. Digital microscopy provided static tissue images captured through the microscope camera and only branched out into digital pathology with the wider availability and adoption of whole slide scanners. Image analysis spans digital microscopy and digital pathology, and image analysis methods had to evolve in parallel with the imaging technologies to address the hypercomplex pathology problems. The complexity of digital pathology problems and research questions increases with every additional stain and scientific discovery. Visiopharm’s team challenged themselves by providing an image analysis solution capable of addressing this hypercomplexity and enabling researchers to advance scientifically with their tool. Artificial Intelligence (AI) capabilities applied to computer vision problems took tissue image analysis to a whole new level and incorporating AI into the Visiopharm software tremendously increased the accessibility of this method. In addition to the two well-known technologies that enabled digital pathology breakthroughs (whole slide imaging and AI), two other important advancements happened during the last two decades · emphasis on interoperability between different digital pathology systems · advances in the field of data visualization. Together these four components are driving the progress of digital pathology both on the diagnostic and research front. During the last 20 years Visiopharm grew significantly, both organically and through funding and they continue creating value and powerful image analysis tools for the tissue image analysis community. Listen to the full episode with Visiopharm’s CEO Michael Grunkin to learn more about this 20-year perspective on what happened in the field of digital microscopy and digital pathology. | |||
| 37: How tissue clearing - based 3D immunofluorescence allows for seeing more biology in the tissue w/ Sharla White, ClearLight Biotechnologies | 07 Feb 2022 | 01:02:17 | |
Even though tissues are tridimensional structures, most tissue research is done on two-dimensional tissue slides. This leaves a tremendous amount of biological information on the table. This episodes' guest - Sharla White, Ph.D., the vice president of research and development at ClearLight Biotechnologies explains how tissue clearing and 3D immunofluorescence can take your tissue research to a whole new level.
Listen to the full episode to learn how Dr. White's team is approaching all the challenges, leveraging CLARITY potential and how this technology changes the way we do tissue research.
Episodes you might also like: | |||
| 36: DICOM standard for pathology annotations. Why do we need it? w/ David Clunie, PixelMed Publishing | 25 Jan 2022 | 00:36:27 | |
The Digital Imaging and Communications in Medicine (DICOM) standard for digital medical imaging has been around since the 1980s. First adopted in radiology it is slowly spreading in pathology as well. Now with image analysis being an integral part of medical imaging workflows, the question arose if the annotations made on the images should have a standard format as well? And can the same DICOM format be used? With deep learning taking over the medical image analysis field, the answer is a definitive yes! Deep learning requires a large number of annotations to train robust image analysis models. Making them requires a lot of time and work and having them in a format that can grant interoperability between different digital pathology and image analysis systems is becoming a requirement. In this episode my guest Dr. David Clunie, the DICOM standard author is explaining what annotations are, why do we need to standardize the format in which they are created, and why the interoperability of digital pathology systems is actually the responsibility of the users of the system and how to be proactive with system vendors to grant it. If you are working in the medical image analysis field or are looking into different image analysis systems that require annotations, this episode is for you! And if you want to learn more about the DICOM standard for images, listen to: Or visit the following resources: | |||
| 35: Digital veterinary cytology and social media teaching w/ Kate Baker, Veterinary Cytology Schoolhouse | 11 Jan 2022 | 00:41:42 | |
In the world of anatomic digital pathology, the mention of digital cytology usually causes thoughts of all the challenges associated with it. We are often not aware that digital pathology and image analysis applications started with digital hematology and cytology (e.g. image analysis-based pap smear evaluation) and that in veterinary medicine digital cytology is a booming discipline. Today’s episode’s guest, Dr. Kate Baker, is a board-certified veterinary clinical pathologist who has embraced the digital cytology journey even before she was doing diagnostic work on whole slide images. Her digital pathology journey started with a Facebook group – Veterinary Cytology Coffee House where she started teaching veterinary cytology with static images. The group kept growing and reached sixty-two thousand members in January 2022. Group members kept asking for more digital cytology resources, so she created two RACE-approved courses for veterinary professionals and a monthly membership site – The Cytology Clubhouse. Currently, she does digital cytology on whole slide images in collaboration with a veterinary laboratory – Scopio. Now confident with digital cytology images she remembers that there was a transition period when she needed her glass slides alongside the digital image to feel confident that she is not missing anything. As she experienced how the glass slides and the digital images consistently carry the same diagnostic information, she needed to consult the glass less and less until it was not necessary anymore. The glass vs digital slide comparison is usually part of the digital pathology system validation and giving pathologists some time to adjust to the new modality with access to both digital images and glass slides during the adjustment period helps them gain confidence and be sure that they are still doing the best job possible. Listen to the full episode to learn about Dr. Kate Baker’s digital cytology journey and explore her digital cytology educational resources:
And check her brilliant educational content on Instagram @clinpathkate. And to gain more insights into the world of digital cytology listen to the podcast episodes below:
Other resources: | |||
| 34: 5 ways to make histopathology image models more robust to domain shift w/ Heather Couture, Pixel Scientia Labs | 29 Dec 2021 | 00:16:32 | |
In this episode, we talk with Heather Couture about how to make deep learning models for tissue image analysis more robust to domain shift.
| |||
| 33: Smart in Media - the virtual microscopy hub w/ Martin Weihrauch MD, Smart in Media | 14 Dec 2021 | 00:38:46 | |
Advanced computer science expertise with the ability to code and a medical degree with over 20 years of clinical experience is a rare combination. This episode’s guest, Martin Weihrauch MD, the co-founder of Smart in Media incorporates this rare combination. His digital pathology platform originated when he was asked by a pharmaceutical company to provide some interactive entertainment for the participants of a medical congress, something beyond just coffee, and the only thing really attracting participants to a company exhibition booth. He decided to host diagnostic quizzes with virtual microscopy. Since then, supported by the close collaboration of a pathologist, Dr. Alberto Peréz Bouza, the platform evolved from the initial virtual microscopy application, through a full pathology educational platform to a fully capable digital pathology diagnostic platform with an open API and the capability for AI algorithm integration. Smart in Media is a digital pathology platform designed by physicians for physicians. The software is optimized for pathology workflow and IT infrastructure. Through the open API, it can communicate with any LIS or LIMS system, has the capability of image analysis algorithm integration, and is extremely user-friendly. Smart in Media users can give real-time feedback to the platform developers about any bugs or difficulties in a user WhatsApp group. Smart in Media is already a leading digital pathology solution provider in Europe with its presence established in Germany, Austria, Switzerland, Italy, the UK, and the Czech Republic, and is the official digital pathology provider of the European Society of Pathology. With its presence expanding to the US the company is striving to bring digital pathology to every pathologist and to improve and speed up their workflow. To learn more about Smart in Media visit their website here. | |||
| 32: Why machine learning expertise is needed for digital pathology projects w/ Heather Couture, Pixel Scientia Labs | 28 Nov 2021 | 00:35:35 | |
What do cancer and climate change have in common? Both are very serious problems and in both, machine learning (ML) and artificial intelligence (AI) can be used to support potential solutions. Even though these AI applications may seem very different the ML methods used to support work on both problems are very similar. Today’s episode’s guest, Heather Couture from Pixel Scientia Labs does exactly that – fights cancer and climate change with AI. She is a computer scientist specializing in computer vision machine learning and deep learning. She started her company during her Ph.D. when she was doing contract work and expanded her work after receiving her degree. She assists companies with accelerating their machine learning projects by distilling and adapting cutting-edge research and applying her over 16 years of experience in the field for analyzing images. Not only does she stay on top of the current research herself, but she also posts about it on LinkedIn several times a week, extracting the most important and actionable information out of the most recent publications on machine learning applications in pathology. Her consulting company gives her the opportunity to optimize her work for impact and get engaged with companies and projects that can really make a difference. Teamwork is important in every area of life, but in the medical domain and especially in pathology it acquires a whole new dimension. No longer is it possible for a single observer to analyze the data in conjunction with the pathology images. The use of computer vision algorithms is often a must and to come up with medically and diagnostically relevant solutions the domain experts from pathology and computer vision need to work together. In clinical settings and in medically focused companies machine learning expertise is necessary to leverage the power of artificial intelligence and apply it to their problems and challenges. Heather supports her clients with such tasks as nuclear detection and classification, mitosis detection, segmentation of different tissue types in pathology images, stain normalization, and other techniques to enable a deep learning model to generalize images from a different scanner. All these things come into a lot of different projects, even if the project endpoints vary. Another important aspect of every deep learning project is data collection and data labeling. Are you working with deep learning for pathology image analysis? If so, visit https://pixelscientia.com/ to learn more about the machine learning expertise you can leverage for your projects. | |||
| 31: AI-powered digital diagnostic tools for medical, veterinary and environmental laboratories. How Techcyte uses AI for digital cytology and smears w/ Ben Cahoon, Techcyte | 03 Nov 2021 | 00:41:38 | |
AI-powered algorithms for digital pathology and tissue image analysis are not new, also digital cytology and hematology already have their share of AI algorithms helping pathologists with faster and more accurate diagnoses. But what about parasitology or microbiology? Techcyte has a tool for that as well.
Reaching phase one will improve patient care significantly. Reaching phase five will revolutionize it.
| |||
| 156: Digital Pathology and AI in Cancer Grading, T-Cell Imaging & Biomarkers | 21 Aug 2025 | 00:34:35 | |
Can AI Grade Cancer Better Than Us? The Truth About T-Cell Imaging, Biomarkers & Digital Pathology Disruption You think Saturday mornings are for coffee? Try diving into bone marrow morphology, organ donor kidney biopsies, and AI-driven metastasis detection at sunrise. That’s how I do it—and you’re invited to join. Welcome to another data-packed episode of DigiPath Digest, where we explore the latest frontier in digital pathology and AI. This time, I reviewed some of the most exciting recent abstracts spanning cancer grading, T-cell quantification, and AI agents in oncology decision-making. These studies aren’t just fascinating—they’re redefining what’s possible in diagnostics, especially in under-resourced areas where digital pathology can create game-changing access and efficiency. 🔬 Highlights with Timestamps [00:04:00] Detecting Metastases with Vision Transformers [00:08:00] DeepHeme: Bone Marrow Smears Meet AI [00:16:00] Multimodal AI for Head & Neck Cancer [00:24:00] Real-Time Kidney Biopsy Evaluation via AI [00:32:00] GPT-4 as an Oncology Agent? 🧠 Resources From This Episode
I’d love to hear your feedback, your projects, and what digital pathology means to you. You can always reach out through comments, LinkedIn, or email. | |||
| 30: Microscope phone adapter that can bring digital pathology to everyone w/ Cade Wilson, Skoped Micro | 18 Oct 2021 | 00:36:19 | |
This episode contains affiliate links. Learn what that means here Have you ever tried to take a picture through your microscope with your smartphone? If you have, you know how much hassle it is to consistently take good, sharp microscope pictures. So maybe, annoyed with how cumbersome it is and how much time it takes, you have already looked for a microscope phone adapter? I know I have, and the one I got from Amazon quickly ended up in my drawer and never saw the light of day again. The pictures were no better than with the handheld phone and it took forever to mount that thing. Disappointed with my Amazon experience I gave up on finding a microscope phone adapter, thinking a proper microscope camera was the only way to go. Then I saw a comment by Skoped Micro on one of my Instagram posts. This microscope phone adapter looked different, and it even featured a dedicated app to take pictures. This is how I met Cade Wilson, a practicing veterinary surgeon from Oklahoma, who developed this unique microscope phone adapter together with the outdoor company Phone Scope, originally modifying it from a phone adapter designed for a hunting spotting scope. Fast forward 5 years and this microscope phone adapter kit consisting of a Custom Phone Case and Microscope Eyepiece Adapter is ready for purchase and anyone who wishes to do digital pathology can do it through their phone with ease, without having to disrupt their workflow or having to spend thousands of dollars for a slide scanner. Listen to the full episode to learn more about how Skoped Micro brings digital pathology to everyone, including veterinary practices, universities, and all other microscope users. So if you need to start doing digital pathology, telepathology, teleteaching, or just want to take beautiful pictures through your microscope for your Instagram or other social media feed, without breaking the bank, look no more! Digital Pathology Place is a proud affiliate of Skoped Micro and you can purchase the digital pathology kit for your phone (consisting of Custom Phone Case and Microscope Eyepiece Adapter) through our affiliate link: Buy the digital pathology kit for your phone here Thank you!
This episode’s resources:
| |||
| 29: An easy AI tool for pathology image analysis. How Aiforia empowers pathologists and scientists with supervised deep learning w/ Tuomas Ropponen, Aiforia | 05 Oct 2021 | 00:39:52 | |
How many times did you get annoyed when using non-intuitive digital pathology software? Have you already given up on digital pathology and image analysis or are you still looking for something powerful but easy to use? Today’s guest, Tuomas Ropponen, the chief technology officer at Aiforia, is talking about the creation of a pathology image analysis platform whose core principles are “easy to use” and “accessible” - Aiforia. Aiforia stands for artificial intelligence (AI) for image analysis (IA) and it combines cloud-based access with supervised deep learning for pathology image analysis. This is where pathologists and computer scientists collaborate closely to create tools that empower pathologists and give them access to the state-of-the-art image analysis methods. Aiforia began as a teaching and telepathology platform for sharing whole slide images. But as soon as deep learning passed the reality check and started outperforming classical computer vision methods, Aiforia’s team knew that they had to incorporate this method into their platform. It would change the way pathology was done. The decision about using supervised deep learning as the method of choice was based on the desire to supervise the teaching of the AI in a similar way as we supervise the teaching of students. Only by supervising and curating the inputs can we be sure that we get quality output. Teaching AI in a supervised manner happens through annotations, and annotations are a natural way that pathologists communicate. Pathologists have always marked areas of interest on the glass and later digital slides. It has always been the way to show others what is important on the tissue. Adapting annotations for supervised deep learning as a way of showing AI what is important was a natural progression of how pathologists work. Another core value at Aiforia is the close collaboration between pathologists and computer scientists. Those two groups currently work very closely together but fostering this open relationship and honest communication required a few iterations and a deeper understanding of each other’s ways of working. For computer scientists, it was surprising that the pathology scoring and grading system often could not be directly reproduced by image analysis algorithms. For pathologists it was surprising that the algorithm results did not match their visual estimates from glass slides. The two groups had to sit together and start dissecting the pathology problems into smaller components as well as translating them into quantifiable tasks. Suddenly it became clear to everyone that the Ki67 quantification in the tumor consists of first detecting the tumor epithelium and later identifying and counting the Ki67 positive and Ki67 negative cells within the epithelium. When pathologists’ fatty liver scores of 70 or 80% were nowhere close to the absolute pixel area of fatty vacuoles in the liver tissue of max 20% it became evident that pathologists were subconsciously normalizing their scores and spreading them on a 0-100% scale. Coming together and analyzing the discrepancies as a team revealed that pathologists’ scores or estimates are often an imprecise and inconsistent benchmark to measure against. Everyone went back to the drawing board (or drawing tablet) and provided a more objective ground truth – annotations. This close collaboration of pathologists and computer scientists as well as involvement of user experience designers helps drive innovation at Aiforia while maintaining accessibility and ease of use. To learn more about AI for image analysis visit Aiforia’s website or even better, let the team show you what this whole thing is about - book a demo. | |||
| 28: QuPath - open source quantitative pathology not only for pathologists w/ Pete Bankhead, University of Edinburgh | 24 Sep 2021 | 00:56:05 | |
With more than 170K total downloads and over 700 citations in scientific literature, QuPath is arguably the most popular open-source software for quantitative pathology and bioimage analysis. Today’s podcast guest, Pete Bankhead, the author of QuPath, is taking us behind the scenes of his software creation. Even though Pete is now a senior lecturer in digital pathology at the University of Edinburgh, his digital pathology career actually started by accident. With an undergraduate degree in theology and a master’s in computer science, he started working on bioimage analysis during his PhD in biomedical sciences. He began using open-source software for image analysis, which was an excellent and very efficient way to work with static bioimages. So, during his post doc work he tried to apply open-source software to pathology whole slide images (WSI), unfortunately without success…The pathology WSI were just too big - it was not even possible to efficiently open them with any openly available software. So he started his own software development – first by creating his own plugins for already available open-source programs, such as ImageJ. It sort of worked but not really… There was no way to coordinate the development and bring all his plugins together, so he started developing his own pathology WSI viewer. That worked, and in the process, he realized that building software tools himself gave him a lot more freedom to solve problems in a way tailored to the specific challenges of digital pathology. He dove deeper into the project and created what we now know as QuPath – the open-source software for digital pathology image analysis. During its development, the software evolved from a Ki67 quantification tool to a machine learning-powered, versatile image analysis software. Listen to the full episode to learn
This episode’s resources:
| |||