Tumor Identification in Colorectal Histology Images Using a Convolutional Neural Network
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Digital Imaging"
DOI: 10.1007/s10278-018-0112-9
Abstract: Colorectal cancer (CRC) is a major global health concern. Its early diagnosis is extremely important, as it determines treatment options and strongly influences the length of survival. Histologic diagnosis can be made by pathologists based… read more here.
Keywords: histology images; histology; convolutional neural; modified vgg ... See more keywords
Att-MoE: Attention-based Mixture of Experts for nuclear and cytoplasmic segmentation
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.06.017
Abstract: Abstract Cell segmentation is a critical step in histology images analysis. Recently, Convolutional Neural Network (CNN) has shown outstanding performance for various segmentation problems, however, the segmentation of histology images remains challenging due to the… read more here.
Keywords: histology images; segmentation; attention; att moe ... See more keywords
Multiplex Cellular Communities in Multi-Gigapixel Colorectal Cancer Histology Images for Tissue Phenotyping
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2020.3023795
Abstract: In computational pathology, automated tissue phenotyping in cancer histology images is a fundamental tool for profiling tumor microenvironments. Current tissue phenotyping methods use features derived from image patches which may not carry biological significance. In… read more here.
Keywords: multiplex cellular; cellular communities; histology; cancer histology ... See more keywords
Identify Representative Samples by Conditional Random Field of Cancer Histology Images
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2022.3198526
Abstract: Pathology analysis is crucial to precise cancer diagnoses and the succeeding treatment plan as well. To detect abnormality in histopathology images with prevailing patch-based convolutional neural networks (CNNs), contextual information often serves as a powerful… read more here.
Keywords: histology images; random field; pathology; conditional random ... See more keywords