Results 1 to 10 of about 202,762 (305)

Deep Learning Based Analysis of Histopathological Images of Breast Cancer [PDF]

Frontiers in Genetics, 2019
Breast cancer is associated with the highest morbidity rates for cancer diagnoses in the world and has become a major public health issue. Early diagnosis can increase the chance of successful treatment and survival. However, it is a very challenging and
Juanying Xie, Chaoyang Zhang, Zhang Chaoyang   +2 more
exaly   +4 more sources

Lung cancer disease prediction with CT scan and histopathological images feature analysis using deep learning techniques

Results in Engineering, 2023
Lung cancer is characterized by the uncontrollable growth of cells in the lung tissues. Early diagnosis of malignant cells in the lungs, which provide oxygen to the human body and excrete carbon dioxide because of important processes, is critical ...
Vani Rajasekar, S Premkumar, S Velliangiri   +2 more
exaly   +3 more sources

Utilizing Detectron2 for accurate and efficient colon cancer detection in histopathological images. [PDF]

Front Bioeng Biotechnol
IntroductionColon cancer ranks among the most prevalent and lethal cancers globally, emphasizing the urgent need for accurate and early diagnostic tools.
Chen L, Shen J, Li X, Li R, Gao X, Chen X, Pan X, Jin X.   +7 more
europepmc   +2 more sources

A multi-task deep learning framework for simultaneous prediction of microsatellite instability and tumor mutational burden in gastric cancer from histopathological images. [PDF]

Front Oncol
BackgroundThe clinical management of gastric cancer (GC) increasingly relies on the biomarkers microsatellite instability (MSI) and tumor mutation burden (TMB) to identify patients likely to benefit from immunotherapy.
Chang Y, Chang H, Lv Y, Xi S, Yang J, Wang B, Zheng X, Xie Y.   +7 more
europepmc   +2 more sources

Research on the Auxiliary Classification and Diagnosis of Lung Cancer Subtypes Based on Histopathological Images

IEEE Access, 2021
Lung cancer (LC) is one of the most serious cancers threatening human health. Histopathological examination is the gold standard for qualitative and clinical staging of lung tumors.
Xiaojian Ma, Chen Chen, Yushuai Yuan
exaly   +3 more sources

Data for glomeruli characterization in histopathological images

Data in Brief, 2020
The data presented in this article is part of the whole slide imaging (WSI) datasets generated in European project AIDPATH 2 This data is also related to the research paper entitle “Glomerulosclerosis Identification in Whole Slide Images using Semantic ...
Gloria Bueno, Lucia Gonzalez-Lopez, Marcial Garcia-Rojo, Arvydas Laurinavicius, Oscar Deniz   +4 more
doaj   +3 more sources

Milker's Nodule: Characteristic Clinical and Histopathological Images. [PDF]

Indian Dermatol Online J
Saraswat N, Tripathy DM, Gopal MM, Mitra DD.   +3 more
europepmc   +2 more sources

Classification and localization of gastric cancer using Multi-Information Fusion Network [PDF]

Revista Română de Informatică și Automatică, 2023
Diagnosing and differentiating gastric cancer cells from stomach ulcers requires high-domain expertise and is time-consuming. Furthermore, medical image processing requires extremely high segmentation accuracy, which may lack interpretability and ...
Varghese Sicily Felix ENIGO, Rajashree SHANMUGANATHAN, Sneha VENKATAPATHY, Sahir RAHAMAN   +3 more
doaj   +1 more source

A Robust Deep Learning-Based Approach for Detection of Breast Cancer from Histopathological Images

Engineering Proceedings, 2023
Breast cancer is a frequently encountered and potentially lethal illness that can affect not only women but also men. It is the most common disease affecting women globally, and is the main cause of morbidity and death.
Raheel Zaman, Ibrar Ali Shah, Naeem Ullah, Gul Zaman Khan   +3 more
doaj   +1 more source

A Multi-Task Convolutional Neural Network for Lesion Region Segmentation and Classification of Non-Small Cell Lung Carcinoma

Diagnostics, 2022
Targeted therapy is an effective treatment for non-small cell lung cancer. Before treatment, pathologists need to confirm tumor morphology and type, which is time-consuming and highly repetitive. In this study, we propose a multi-task deep learning model
Zhao Wang, Yuxin Xu, Linbo Tian, Qingjin Chi, Fengrong Zhao, Rongqi Xu, Guilei Jin, Yansong Liu, Junhui Zhen, Sasa Zhang   +9 more
doaj   +1 more source