Automated Histology Analysis Opportunities
Histology is the microscopic inspection of plant or animal tissue. It is a critical component in diagnostic medicine and a tool for studying the pathogenesis and biology of processes such as cancer and embryogenesis. Tissue processing for histology has become increasingly automated, drastically increasing the speed at which histology labs can produce tissue slides for viewing. Another trend is the digitization of these slides, allowing them to be viewed on a computer rather than through a microscope.
Despite these changes, much of the routine analysis of tissue sections remains a painstaking, manual task that can only be completed by highly trained pathologists at a high cost per hour. There is, therefore, a niche for image analysis methods that can automate some aspects of this analysis. These methods could also automate tasks that are prohibitively time-consuming for humans, e.g., discovering new disease markers from hundreds of whole-slide images(WSIs) or precisely quantifying tissues within a tumor.
Related Matlab Project Titles:
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- Toward a Morphodynamic Model of the Cell: Signal processing for cell modeling.
- Binary Tomography Reconstructions With Stochastic Level-Set Methods.
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- Reconstruction of Fluorophore Concentration Variation in Dynamic Fluorescence Molecular Tomography.
- Discriminative Clustering and Feature Selection for Brain MRI Segmentation.
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- Active Contour-Based Cell Segmentation During Freezing and Its Application in Cryopreservation.
- Automatic Segmentation of Trophectoderm in Microscopic Images of Human Blastocysts.
- Automatic 3-D Segmentation of Endocardial Border of the Left Ventricle From Ultrasound Images.
- Electronic Cleansing in Fecal-Tagging Dual-Energy CT Colonography Based on Material Decomposition and Virtual Colon Tagging.
- Signal Processing Challenges in Quantitative 3-D Cell Morphology: More than meets the eye.
- In Vivo Ultrasound Thermography in Presence of Temperature Heterogeneity and Natural Motions.
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