A new approach to develop computer-aided diagnosis scheme of breast mass classification using deep learning technology
PURPOSE: To develop and test a deep learning based computer-aided diagnosis (CAD)
scheme of mammograms for classifying between malignant and benign masses. METHODS …
scheme of mammograms for classifying between malignant and benign masses. METHODS …
Added value of radiomics on mammography for breast cancer diagnosis: a feasibility study
N Mao, P Yin, Q Wang, M Liu, J Dong, X Zhang… - Journal of the American …, 2019 - Elsevier
Background This study aimed to evaluate whether radiomics can improve the diagnostic
performance of mammography compared with that obtained by experienced radiologists …
performance of mammography compared with that obtained by experienced radiologists …
Classification of breast masses using a computer-aided diagnosis scheme of contrast enhanced digital mammograms
Contrast-enhanced digital mammography (CEDM) is a promising imaging modality in breast
cancer diagnosis. This study aims to investigate how to optimally develop a computer-aided …
cancer diagnosis. This study aims to investigate how to optimally develop a computer-aided …
Improving mammography lesion classification by optimal fusion of handcrafted and deep transfer learning features
Objective. Handcrafted radiomics features or deep learning model-generated automated
features are commonly used to develop computer-aided diagnosis schemes of medical …
features are commonly used to develop computer-aided diagnosis schemes of medical …
Improving the performance of computer-aided classification of breast lesions using a new feature fusion method
Computer-Aided Diagnosis (CAD) schemes used to classify suspicious breast lesions
typically include machine learning classifiers that are trained using features computed from …
typically include machine learning classifiers that are trained using features computed from …
Developing global image feature analysis models to predict cancer risk and prognosis
In order to develop precision or personalized medicine, identifying new quantitative imaging
markers and building machine learning models to predict cancer risk and prognosis has …
markers and building machine learning models to predict cancer risk and prognosis has …
Improving performance of breast cancer risk prediction using a new CAD-based region segmentation scheme
Objective of this study is to develop and test a new computer-aided detection (CAD) scheme
with improved region of interest (ROI) segmentation combined with an image feature …
with improved region of interest (ROI) segmentation combined with an image feature …
[PDF][PDF] Developing Novel Computer Aided Diagnosis Schemes for Improved Classification of Mammography Detected Masses
M Jones - 2023 - core.ac.uk
Breast cancer has the highest incident rate and second highest mortality rate among
cancers in women [97]. Routine mammographic screening is considered a widely used cost …
cancers in women [97]. Routine mammographic screening is considered a widely used cost …
A hybrid deep learning approach to predict malignancy of breast lesions using mammograms
Y Wang, M Heidari… - Medical Imaging …, 2018 - spiedigitallibrary.org
Applying deep learning technology to medical imaging informatics field has been recently
attracting extensive research interest. However, the limited medical image dataset size often …
attracting extensive research interest. However, the limited medical image dataset size often …
Comparison of two-dimensional synthesized mammograms versus original digital mammograms: A quantitative assessment
M Tan, M Al-Shabi, WY Chan, L Thomas… - Medical & biological …, 2021 - Springer
This study objectively evaluates the similarity between standard full-field digital
mammograms and two-dimensional synthesized digital mammograms (2DSM) in a cohort of …
mammograms and two-dimensional synthesized digital mammograms (2DSM) in a cohort of …