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 as different cancer types. They provide a detailed view of different types of diseases and their tissue status. These images are an essential resource with which to define biological compositions or analyze cell and tissue structures. This imaging modality is very important for diagnostic applications. The analysis of histopathology images is a prolific and relevant research area supporting disease diagnosis. In this paper, the challenges of histopathology image analysis are evaluated. An extensive review of conventional and deep learning techniques which have been applied in histological image analyses is presented. This review summarizes many current datasets and highlights important challenges and constraints with recent deep learning techniques, alongside possible future research avenues. Despite the progress made in this research area so far, it is still a significant area of open research because of the variety of imaging techniques and disease-specific characteristics.
Code (0)
등록된 구현이 없습니다.
Tasks
BIG-bench Machine LearningDiagnosticSimilar Papers 제목 키워드 기반
Machine learning methods for histopathological image analysis
Abundant accumulation of digital histopathological images has led to the increased demand for their analysis, such as computer-aided diagnosis using machine learning techniques. However, digital pathological images and r…
BIG-bench Machine LearningMachine 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 not only time and resource consuming, but also very challenging even for exper…
BIG-bench Machine LearningTexture CNN for Histopathological Image Classification
Biopsies are the gold standard for breast cancer diagnosis. This task can be improved by the use of Computer Aided Diagnosis (CAD) systems, reducing the time of diagnosis and reducing the inter and intra-observer variabi…
ClassificationGeneral ClassificationHistopathological Image Classificationimage-classification+1A Comparative Analysis of Image Descriptors for Histopathological Classification of Gastric Cancer
Gastric cancer ranks as the fifth most common and fourth most lethal cancer globally, with a dismal 5-year survival rate of approximately 20%. Despite extensive research on its pathobiology, the prognostic predictability…
DiagnosticEBHI:A New Enteroscope Biopsy Histopathological H&E Image Dataset for Image Classification Evaluation
Background and purpose: Colorectal cancer has become the third most common cancer worldwide, accounting for approximately 10% of cancer patients. Early detection of the disease is important for the treatment of colorecta…
image-classificationImage Classification