Digital Imaging for Blood Diseases

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Moved, week to 23 Oct 2026: 0
Papers in 60 days: 8

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A Dataset of Human Sperm Microscopy Videos for Detection, Tracking, and Motility Parameter Analysis
bioRxiv · 16 Oct 2026 · Preprint
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https://jclub.com.au/a/10.64898/2025.12.15.694470
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Quantitative Facial Phenotyping and Age-Associated Differences in Sickle Cell Disease Using Interpretable Machine Learning
medRxiv · 16 Oct 2026 · Preprint
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https://jclub.com.au/a/10.64898/2026.03.03.26346563
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EventHorizon: A Foundation Model for Clinical Flow Cytometry
bioRxiv · 10 Oct 2026 · Preprint
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https://jclub.com.au/a/10.64898/2026.06.18.733197
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SmartHisto: Bayesian active learning for histology images.
PLOS Computational Biology · 17 Sept 2026 · Journal Article
SmartHisto achieves a mean IoU of 0.75 in histology image segmentation, outperforming competitors by over 25% and reducing annotation needs significantly.
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https://jclub.com.au/a/42752439
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PSD-95 drives binocular vision maturation critical for predation
bioRxiv · 11 Sept 2026 · Preprint
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https://jclub.com.au/a/10.1101/2025.10.22.683936
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Generating cell-level protein-expression labels on HE from serial-section immunohistochemistry, with ground-truth-free quality control
bioRxiv · 3 Sept 2026 · Preprint
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https://jclub.com.au/a/10.64898/2026.06.18.733058
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Counterfactual Diffusion Models Provide Interpretable Explanations of Artificial Intelligence Models in Pathology.
Cancer Research · 2 Sept 2026 · Journal Article
Counterfactual diffusion models like MoPaDi enable interpretable explanations by revealing morphological features linked to AI predictions in pathology, with 4 datasets spanning multiple cancers.
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https://jclub.com.au/a/42308255
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U-Net Ensembles for Segmentation of High-Density Cell Populations and Organelles
bioRxiv · 26 Aug 2026 · Preprint
Ensemble U-Net models achieve state-of-the-art segmentation of high-density platelets and organelles in 3D electron microscopy datasets, enabling detailed morphological analysis.
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https://jclub.com.au/a/10.1101/2024.11.19.623228
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