Machine learning methods for histopathological image analysis: A review
Histopathological images (HIs) are the gold standard for evaluating some types of tumors for
cancer diagnosis. The analysis of such images is time and resource-consuming and very …
cancer diagnosis. The analysis of such images is time and resource-consuming and very …
Histopathologic image processing: A review
Histopathologic Images (HI) are the gold standard for evaluation of some tumors. However,
the analysis of such images is challenging even for experienced pathologists, resulting in …
the analysis of such images is challenging even for experienced pathologists, resulting in …
A comprehensive review of the deep learning-based tumor analysis approaches in histopathological images: segmentation, classification and multi-learning tasks
Medical Imaging has become a vital technique that has been embraced in the diagnosis and
treatment process of cancer. Histopathological slides, which microscopically examine the …
treatment process of cancer. Histopathological slides, which microscopically examine the …
Recent advances of deep learning for computational histopathology: principles and applications
Simple Summary The histopathological image is widely considered as the gold standard for
the diagnosis and prognosis of human cancers. Recently, deep learning technology has …
the diagnosis and prognosis of human cancers. Recently, deep learning technology has …
Objective diagnosis for histopathological images based on machine learning techniques: Classical approaches and new trends
Histopathology refers to the examination by a pathologist of biopsy samples. Histopathology
images are captured by a microscope to locate, examine, and classify many diseases, such …
images are captured by a microscope to locate, examine, and classify many diseases, such …
Machine learning approaches for pathologic diagnosis
D Komura, S Ishikawa - Virchows Archiv, 2019 - Springer
Abstract Machine learning techniques, especially deep learning techniques such as
convolutional neural networks, have been successfully applied to general image …
convolutional neural networks, have been successfully applied to general image …
Deep learning in histopathology: A review
Histopathology is diagnosis based on visual examination of tissue sections under a
microscope. With the growing number of digitally scanned tissue slide images, computer …
microscope. With the growing number of digitally scanned tissue slide images, computer …
HEAL: an automated deep learning framework for cancer histopathology image analysis
Motivation Digital pathology supports analysis of histopathological images using deep
learning methods at a large-scale. However, applications of deep learning in this area have …
learning methods at a large-scale. However, applications of deep learning in this area have …
AI-based carcinoma detection and classification using histopathological images: A systematic review
Histopathological image analysis is the gold standard to diagnose cancer. Carcinoma is a
subtype of cancer that constitutes more than 80% of all cancer cases. Squamous cell …
subtype of cancer that constitutes more than 80% of all cancer cases. Squamous cell …
[HTML][HTML] Pathology image analysis using segmentation deep learning algorithms
With the rapid development of image scanning techniques and visualization software, whole
slide imaging (WSI) is becoming a routine diagnostic method. Accelerating clinical diagnosis …
slide imaging (WSI) is becoming a routine diagnostic method. Accelerating clinical diagnosis …