AIMC Topic: Hematoxylin
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Deep Learning for Predicting Effect of Neoadjuvant Therapies in Non-Small Cell Lung Carcinomas With Histologic Images.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Aug 12, 2023
Neoadjuvant therapies are used for locally advanced non-small cell lung carcinomas, whereby pathologists histologically evaluate the effect using resected specimens. Major pathological response (MPR) has recently been used for treatment evaluation an...
Automated diagnosis of 7 canine skin tumors using machine learning on H&E-stained whole slide images.
Veterinary pathology
Jul 29, 2023
Microscopic evaluation of hematoxylin and eosin-stained slides is still the diagnostic gold standard for a variety of diseases, including neoplasms. Nevertheless, intra- and interrater variability are well documented among pathologists. So far, compu...
Deep Learning-Based Stratification of Gastric Cancer Patients from Hematoxylin and Eosin-Stained Whole Slide Images by Predicting Molecular Features for Immunotherapy Response.
The American journal of pathology
Jun 24, 2023
Determining the molecular characteristics of cancer patients is crucial for optimal immunotherapy decisions. The aim of this study was to screen immunotherapy beneficiaries by predicting key molecular features from hematoxylin and eosin-stained image...
Fully Automated Tumor Bud Assessment in Hematoxylin and Eosin-Stained Whole Slide Images of Colorectal Cancer.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
May 30, 2023
Tumor budding (TB), the presence of single cells or small clusters of up to 4 tumor cells at the invasive front of colorectal cancer (CRC), is a proven risk factor for adverse outcomes. International definitions are necessary to reduce interobserver ...
Domain-specific transfer learning in the automated scoring of tumor-stroma ratio from histopathological images of colorectal cancer.
PloS one
May 26, 2023
Tumor-stroma ratio (TSR) is a prognostic factor for many types of solid tumors. In this study, we propose a method for automated estimation of TSR from histopathological images of colorectal cancer. The method is based on convolutional neural network...
Deep-Learning-Based Hepatic Ploidy Quantification Using H&E Histopathology Images.
Genes
Apr 16, 2023
Polyploidy, the duplication of the entire genome within a single cell, is a significant characteristic of cells in many tissues, including the liver. The quantification of hepatic ploidy typically relies on flow cytometry and immunofluorescence (IF) ...
A Deep Learning-Based System Trained for Gastrointestinal Stromal Tumor Screening Can Identify Multiple Types of Soft Tissue Tumors.
The American journal of pathology
Apr 15, 2023
The accuracy and timeliness of the pathologic diagnosis of soft tissue tumors (STTs) critically affect treatment decision and patient prognosis. Thus, it is crucial to make a preliminary judgement on whether the tumor is benign or malignant with hema...
A novel dataset and efficient deep learning framework for automated grading of renal cell carcinoma from kidney histopathology images.
Scientific reports
Apr 7, 2023
Trends of kidney cancer cases worldwide are expected to increase persistently and this inspires the modification of the traditional diagnosis system to respond to future challenges. Renal Cell Carcinoma (RCC) is the most common kidney cancer and resp...
Interpretable deep learning model to predict the molecular classification of endometrial cancer from haematoxylin and eosin-stained whole-slide images: a combined analysis of the PORTEC randomised trials and clinical cohorts.
The Lancet. Digital health
Dec 7, 2022
BACKGROUND: Endometrial cancer can be molecularly classified into POLE, mismatch repair deficient (MMRd), p53 abnormal (p53abn), and no specific molecular profile (NSMP) subgroups. We aimed to develop an interpretable deep learning pipeline for whole...
Artificial intelligence workflow quantifying muscle features on Hematoxylin-Eosin stained sections reveals dystrophic phenotype amelioration upon treatment.
Scientific reports
Nov 19, 2022
Cell segmentation is a key step for a wide variety of biological investigations, especially in the context of muscle science. Currently, automated methods still struggle to perform skeletal muscle fiber quantification on Hematoxylin-Eosin (HE) staine...
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