Results 201 to 210 of about 77,670 (220)

Cross-View Correspondence Reasoning Based on Bipartite Graph Convolutional Network for Mammogram Mass Detection

Computer Vision and Pattern Recognition, 2020
Mammogram mass detection is of great clinical significance due to its high proportion in breast cancers. The information from cross views (i.e., mediolateral oblique and cranio-caudal) is highly related and complementary, and is helpful to make ...
Yuhang Liu, Fandong Zhang, Qianyi Zhang, Siwen Wang, Yizhou Wang, Yizhou Yu   +5 more
semanticscholar   +1 more source

Intuitionistic fuzzy approach for enhancement of low contrast mammogram images

International journal of imaging systems and technology (Print), 2020
Mammogram image enhancement is very much necessary in diagnosing breast cancer or tumor at an early stage. Nonuniform illumination and low contrast images are commonly encountered in mammogram images.
Tamalika Chaira
semanticscholar   +1 more source

Conditional Infilling GANs for Data Augmentation in Mammogram Classification

RAMBO+BIA+TIA@MICCAI, 2018
Deep learning approaches to breast cancer detection in mammograms have recently shown promising results. However, such models are constrained by the limited size of publicly available mammography datasets, in large part due to privacy concerns and the ...
E. Wu, Kevin Wu, David D. Cox, William Lotter   +3 more
semanticscholar   +1 more source

A Multi-scale CNN and Curriculum Learning Strategy for Mammogram Classification

DLMIA/ML-CDS@MICCAI, 2017
Screening mammography is an important front-line tool for the early detection of breast cancer, and some 39 million exams are conducted each year in the United States alone.
William Lotter, Greg Sorensen, David D. Cox   +2 more
semanticscholar   +1 more source

Enhance the Mammogram Images for Both Segmentation and Feature Extraction Using Wavelet Transform

2019 International Conference on Advanced Science and Engineering (ICOASE), 2019
Breast cancer (BC) is a main killer disease for women and men. It can be cured and controlled only if it is detected at its early detection. BC initial identification can be realized by the help of computer support identification approaches.
D. A. Zebari, H. Haron, Subhi R. M. Zeebaree, Diyar Qader Zeebaree   +3 more
semanticscholar   +1 more source

Multimodal classification of breast cancer using feature level fusion of mammogram and ultrasound images in machine learning paradigm

Multim. Tools Appl., 2023
Kushangi Atrey, B. K. Singh, N. Bodhey
semanticscholar   +1 more source

Deep Learning Based Capsule Neural Network Model for Breast Cancer Diagnosis Using Mammogram Images

Interdisciplinary Sciences Computational Life Sciences, 2021
T. Kavitha, Paul P. Mathai, C. Karthikeyan, M. Ashok, R. Kohar, J. Avanija, S. Neelakandan   +6 more
semanticscholar   +1 more source

Mammogram Image Enhancement Using Entropy and CLAHE Based Intuitionistic Fuzzy Method

SPIN, 2019
Mortality rate because of breast cancer diminishes to a large extent if the categorization of breast lesions as malignant or benign is done properly. But this process is quite complicated owing to erroneous detection of noise pixels as false positives ...
Jyoti Dabass, Shaveta Arora, R. Vig, M. Hanmandlu   +3 more
semanticscholar   +1 more source

A novel feature selection framework based on grey wolf optimizer for mammogram image analysis

Neural computing & applications (Print), 2021
B. Sathiyabhama, S. U. Kumar, J. Jayanthi, Thanikachalam Sathiya, A. K. Ilavarasi, V. Yuvarajan, K. Gopikrishna   +6 more
semanticscholar   +1 more source