Histopathological Image
Histopathological image analysis focuses on extracting meaningful information from microscopic images of tissue samples, primarily to aid in disease diagnosis and prognosis. Current research heavily utilizes deep learning, employing convolutional neural networks (CNNs), transformers, and graph neural networks (GNNs) for tasks like image segmentation, classification, and multimodal data integration (e.g., combining H&E and immunofluorescence images, or integrating genomic data). These advancements are significantly impacting healthcare by improving diagnostic accuracy, accelerating workflows, and potentially enabling more personalized medicine through improved prediction of treatment response and disease progression.
Papers
Immunohistochemistry Biomarkers-Guided Image Search for Histopathology
Abubakr Shafique, Morteza Babaie, Ricardo Gonzalez, H. R. Tizhoosh
Composite Biomarker Image for Advanced Visualization in Histopathology
Abubakr Shafique, Morteza Babaie, Ricardo Gonzalez, Adrian Batten, Soma Sikdar, H. R. Tizhoosh