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Computational Pathology Fundamentals
2-Day Course Agenda
Duration: 2 Days | Target Audience: Pathologists | Date: 18-19 August 2026
Sponsoring the Diagnexia Histopathology Symposium 2023
DAY 1: Foundations of Computational Pathology
Time
Session
Description
Morning Session
09:30 – 10:00
Registration & Coffee
Sign-in, materials collection, networking
10:00 – 10:30
Welcome & Introduction to Computational Pathology
Prof. Runjan Chetty Chief Medical Officer at Deciphex/Diagnexia
Pierre Moulin MD, PhD — Chief Scientific Officer @ Deciphex
Pierre Moulin MD, PhD — Chief Scientific Officer @ Deciphex
Course overview and learning objectives; definition and scope of computational pathology; distinction from digital pathology; the data-intensive nature of pathology; course roadmap
10:30 – 11:15
Digital Image Fundamentals I: Core Concepts
Pierre Moulin MD, PhD — Chief Scientific Officer @ Deciphex
What is a digital image; pixels, resolution, and bit depth; color spaces (RGB, HSV, LAB); relationship between magnification and microns per pixel (mpp); image file formats (JPEG, PNG, TIFF); lossy vs. lossless compression and their impact on analysis; why format choices matter downstream
11:15 – 11:30
Coffee Break
11:30 – 12:15
Digital Image Fundamentals II: Whole-Slide Imaging
Pierre Moulin MD, PhD — Chief Scientific Officer @ Deciphex
Whole-slide imaging technology; scanner types and acquisition; pyramidal/multi-resolution image structure; proprietary vs. open WSI formats (SVS, NDPI, DICOM WSI); storage, memory, and bandwidth considerations; practical implications for computational pipelines
12:15 – 13:00
Stain Physics and Color Analysis
Andrew Janowczyk Assistant Professor at Emory University
Physics of stain absorption (Beer-Lambert law); H&E and special stains from a computational perspective; stain vectors and color deconvolution; stain normalization approaches; quantification of chromogenic and fluorescent signals; inter-laboratory variability challenges
13:00 – 14:00
Lunch Break
Afternoon Session
14:00 – 14:45
Image Processing Fundamentals
Andrew Janowczyk Assistant Professor at Emory University
Intensity transformations; histogram processing; spatial filtering (smoothing and sharpening); morphological operations (erosion, dilation, opening, closing); practical applications in tissue analysis
14:45 – 15:30
Segmentation in Pathology
Pierre Moulin MD, PhD — Chief Scientific Officer @ Deciphex
Tissue vs. background detection; thresholding methods (global, Otsu’s, adaptive); region-based and edge-based approaches; nuclear and cell segmentation; the reference area problem
15:30 – 15:45
Coffee Break
15:30 – 15:45
Feature Extraction: Classical Approaches
Andrew Janowczyk Assistant Professor at Emory University
Morphological features (size, shape, texture); nuclear and cellular descriptors; glandular and architectural features; tumor microenvironment metrics; building interpretable feature sets
14.30-15.00
Introduction to Machine Learning for Pathology
Andrew Janowczyk Assistant Professor at Emory University
Supervised vs. unsupervised learning; training, validation, and test sets; classical methods (random forests, SVM); performance metrics and their clinical interpretation; avoiding common pitfalls
15.05-15.35
Introduction to Deep Learning
Neural network fundamentals; forward propagation and backpropagation (conceptual); activation functions; loss functions and optimization; regularisation techniques; training vs. inference; why deep learning transformed computational pathology
15.40-16.10
Day 1 Wrap-up and Q&A
Summary of key concepts; preview of Day 2; open questions
28
Sponsoring the Diagnexia Histopathology Symposium 2023
DAY 2: Advanced Topics and Clinical Applications
Time
Session
Description
Morning Session
08:30 – 09:00
Coffee & Networking
09:00 – 09:15
Day 1 Recap and Day 2 Overview - PM
Pierre Moulin MD, PhD — Chief Scientific Officer @ Deciphex
Brief review of foundational concepts; outline of advanced topics
09:15 – 10:00
Deep Learning Architectures for Pathology
Emre Köse Computational Pathologist @ Deciphex
Convolutional neural networks (CNNs) explained; landmark architectures (ResNet, U-Net); Vision Transformers (ViT); classification, segmentation, and detection networks; transfer learning and domain adaptation
10:00 – 10:45
Training Strategies and Data Challenges
Andrew Janowczyk Assistant Professor at Emory University
Data preparation and patch extraction; annotation strategies and quality; handling class imbalance; data augmentation (geometric, color, stain); managing staining and scanner variability
10:45 – 11:00
Coffee Break
11:00 – 11:45
Multiple Instance Learning and Slide-Level Prediction
John Weldon Clinical AI Director @ Deciphex
The MIL paradigm for whole-slide analysis; attention-based aggregation; weakly supervised learning; from patches to patient-level predictions
11:45 – 12:30
Foundation Models and Vision-Language Models
Emre Köse Computational Pathologist @ Deciphex
Self-supervised and contrastive learning; pathology foundation models (overview); vision-language models (CLIP, PathChat, CONCH); zero-shot classification; conversational AI for pathology; limitations and hallucination risks
12:30 – 12:45
Morning Q&A
12:45 – 13:45
Lunch Break
Afternoon Session
13:45 – 14:30
Clinical Applications I: Diagnostic Support
Andrew Janowczyk Assistant Professor at Emory University
Cancer detection and classification (breast, prostate, colorectal, lung); Gleason grading automation; metastasis detection; quality control and triage applications; discussion on clinical utility
14:30 – 15:15
Segmentation in Pathology
John Weldon Clinical AI Director @ Deciphex
IHC quantification (Ki-67, HER2, PD-L1); tumor microenvironment analysis; TIL assessment; predicting molecular features from H&E; survival and treatment response prediction; discussion on clinical utility
15:15 – 15:30
Coffee Break
15:30 – 16:00
Validation, Regulation, and Deployment
Jonathan Armstrong AI Governance Lead @ Deciphex
Evaluation metrics for classification, segmentation, detection; cross-validation and external validation; regulatory pathways (FDA, CE/MDR); algorithmic fairness and bias considerations; clinical integration and continuous monitoring
16:00 – 16:30
Model Interpretability and Explainable
Andrew Janowczyk Assistant Professor at Emory University
Emre Köse Computational Pathologist @ Deciphex
Why interpretability matters in clinical pathology; XAI techniques (saliency maps, Grad-CAM, attention visualization); accuracy vs. interpretability trade-offs; building pathologist trust
16:30 – 17:00
Future Directions and the Pathologist’s Role
Andrew Janowczyk Assistant Professor at Emory University
Multiplex imaging analysis (mIF, IMC, spatial transcriptomics); multimodal data integration; federated learning; AI-augmented pathology workflows
17:00 – 17:30
Emerging Technologies
Pierre Moulin MD, PhD — Chief Scientific Officer @ Deciphex
The pathologist’s role in computational pathology development; integration of imaging with -omics data; AI-assisted reporting and case management; building multidisciplinary collaborations; career pathways and skill development
17:30 – 18:00
Open Discussion, Q&A, and Closing
Panel discussion; participant questions; key takeaways; resources for continued learning; course evaluation; closing remarks
28
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DON’T MISS OUT
Don’t miss the 2026 Diagnexia Computational Pathology Fundamentals course — a rare opportunity to learn directly from leading experts, sharpen diagnostic skills, and exchange insights with peers in the historic setting of The Queen’s College, Oxford.
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