Precision Pathology
From Pixels to Predictions
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Beschreibung
Pathology has always been rooted in the art of seeing—of discerning meaning in the smallest details of tissue and stain. Yet the field now stands at a defining crossroads. Precision Pathology: Pixels to Predictions explores this moment of transformation with exceptional clarity, revealing how digital pathology, artificial intelligence especially the recent advancements in generative and foundation models, agentic AI, and multi‑omics are reshaping not only how we diagnose disease, but how we understand it. The book offers a timely and comprehensive synthesis of where computational pathology stands today and where it is poised to go next. Crucially, it does so with a strong grounding in real-world pathology workflows while maintaining a clear and ambitious vision for the future.
By reframing the slide as more than a visual artifact, the authors introduce pixelomics, a practical framework that traces the journey from raw pixels to learned patterns, and ultimately to diagnosis, prediction, and molecular insights. This progression illuminates how modern computer vision can uncover signals hidden in the pixelome.
This book looks ahead to a future in which diagnosis is only one step in a broader continuum of care. With pathology increasingly central to treatment selection, prognostication, and precision medicine, the need for reproducibility and standardization has never been greater. Here, AI offers not just efficiency, but the possibility of reducing interpretive variability across observers and institutions. Precision Pathology: Pixels to Predictions serves as a guide and an invaluable resource for practicing pathologists, trainees, researchers, and all those invested in the future of the field and want to navigate the evolution of Precision Pathology from microscope to agentic systems, unlocking the hidden biology within every pixel.
Pathology has always been rooted in the art of seeing—of discerning meaning in the smallest details of tissue and stain. Yet the field now stands at a defining crossroads. Precision Pathology: Pixels to Predictions explores this moment of transformation with exceptional clarity, revealing how digital pathology, artificial intelligence especially the recent advancements in generative and foundation models, agentic AI , and multi‑omics are reshaping not only how we diagnose disease, but how we understand it. The book offers a timely and comprehensive synthesis of where computational pathology stands today and where it is poised to go next. Crucially, it does so with a strong grounding in real-world pathology workflows while maintaining a clear and ambitious vision for the future.
By reframing the slide as more than a visual artifact, the authors introduce pixelomics, a practical framework that traces the journey from raw pixels to learned patterns, and ultimately to diagnosis, prediction, and molecular insights. This progression illuminates how modern computer vision can uncover signals hidden in the pixelome.
This book looks ahead to a future in which diagnosis is only one step in a broader continuum of care. With pathology increasingly central to treatment selection, prognostication, and precision medicine, the need for reproducibility and standardization has never been greater. Here, AI offers not just efficiency, but the possibility of reducing interpretive variability across observers and institutions. Precision Pathology: Pixels to Predictions serves as a guide and an invaluable resource for practicing pathologists, trainees, researchers, and all those invested in the future of the field and want to navigate the evolution of Precision Pathology from microscope to agentic systems, unlocking the hidden biology within every pixel.
Structured to guide readers through the fundamental concepts of precision pathology through a pixelomics framework Topics include image acquisition techniques, analytical methods including the latest foundation model, and their impact Valuable for practicing pathologists, trainees, computer scientists, researchers, and all those interested in the field
Autor*in
Ehsan Ullah
Themen in »Precision Pathology«
imagomics Immunohistochemistry Tissue preparation Anatomical pathology deep learning models tissue diagnoses novel biomarkers Special stains Digital Pathology datasets Whole Slide Imaging Biomarkers Machine Learning Computational Methods Image-Based Pathology