Recent advances and clinical applications of deep learning in medical image analysis
Deep learning has received extensive research interest in develo** new medical image
processing algorithms, and deep learning based models have been remarkably successful …
processing algorithms, and deep learning based models have been remarkably successful …
Breast cancer segmentation methods: current status and future potentials
Early breast cancer detection is one of the most important issues that need to be addressed
worldwide as it can help increase the survival rate of patients. Mammograms have been …
worldwide as it can help increase the survival rate of patients. Mammograms have been …
Computer-aided diagnosis with deep learning architecture: applications to breast lesions in US images and pulmonary nodules in CT scans
This paper performs a comprehensive study on the deep-learning-based computer-aided
diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by …
diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by …
A deep learning framework for supporting the classification of breast lesions in ultrasound images
A deep learning framework for supporting the classification of breast lesions in ultrasound
images - IOPscience Skip to content IOP Science home Accessibility Help Search Journals …
images - IOPscience Skip to content IOP Science home Accessibility Help Search Journals …
Approaches for automated detection and classification of masses in mammograms
HD Cheng, XJ Shi, R Min, LM Hu, XP Cai, HN Du - Pattern recognition, 2006 - Elsevier
Breast cancer continues to be a significant public health problem in the world. Early
detection is the key for improving breast cancer prognosis. Mammography has been one of …
detection is the key for improving breast cancer prognosis. Mammography has been one of …
A review of automatic mass detection and segmentation in mammographic images
The aim of this paper is to review existing approaches to the automatic detection and
segmentation of masses in mammographic images, highlighting the key-points and main …
segmentation of masses in mammographic images, highlighting the key-points and main …
AUNet: attention-guided dense-upsampling networks for breast mass segmentation in whole mammograms
Mammography is one of the most commonly applied tools for early breast cancer screening.
Automatic segmentation of breast masses in mammograms is essential but challenging due …
Automatic segmentation of breast masses in mammograms is essential but challenging due …
Anniversary Paper: History and status of CAD and quantitative image analysis: The role of Medical Physics and AAPM
The roles of physicists in medical imaging have expanded over the years, from the study of
imaging systems (sources and detectors) and dose to the assessment of image quality and …
imaging systems (sources and detectors) and dose to the assessment of image quality and …
Breast image analysis for risk assessment, detection, diagnosis, and treatment of cancer
The role of breast image analysis in radiologists' interpretation tasks in cancer risk
assessment, detection, diagnosis, and treatment continues to expand. Breast image analysis …
assessment, detection, diagnosis, and treatment continues to expand. Breast image analysis …
[PDF][PDF] Computer-aided detection and diagnosis in mammography
The American Cancer Society estimates that 215,990 women will be diagnosed with breast
cancer in the United States in 2004 [1]. Another 40,110 women will die of the disease. In the …
cancer in the United States in 2004 [1]. Another 40,110 women will die of the disease. In the …