A pathomic approach for tumor-infiltrating lymphocytes classification on breast cancer digital pathology images
Background and objectives The detection of tumor-infiltrating lymphocytes (TILs) could aid in
the development of objective measures of the infiltration grade and can support decision …
the development of objective measures of the infiltration grade and can support decision …
Machine learning–based prediction of pediatric ulcerative colitis treatment response using diagnostic histopathology
The initial presentation of ulcerative colitis within the pediatric population exhibits a degree
of uniformity, the majority characterized by extensive colitis at the time of diagnosis …
of uniformity, the majority characterized by extensive colitis at the time of diagnosis …
Exploratory Analysis of Radiomics and Pathomics in Uterine Corpus Endometrial Carcinoma
Uterine corpus endometrial carcinoma (EC) is one of the most common malignancies in the
female reproductive system, characterized by tumor heterogeneity at both radiological and …
female reproductive system, characterized by tumor heterogeneity at both radiological and …
Deep Learning-Based Cellular Nuclei Segmentation Using Transformer Model
M Erezman, T Dziubich - European Conference on Advances in Databases …, 2024 - Springer
Accurate segmentation of cellular nuclei is imperative for various biological and medical
applications, such as cancer diagnosis and drug discovery. Histopathology, a discipline …
applications, such as cancer diagnosis and drug discovery. Histopathology, a discipline …
RadPleura: a Radiomics-based Framework for Lung Pleura Classification in Histology Images from Interstitial Lung Diseases
Lung pleura is a reference structure for the identification of histological characteristics for the
recognition of a pathological interstitial lung disease (ILD) pattern. When a pattern is found, it …
recognition of a pathological interstitial lung disease (ILD) pattern. When a pattern is found, it …