Breast tumor localization and segmentation using machine learning techniques: Overview of datasets, findings, and methods
Abstract The Global Cancer Statistics 2020 reported breast cancer (BC) as the most
common diagnosis of cancer type. Therefore, early detection of such type of cancer would …
common diagnosis of cancer type. Therefore, early detection of such type of cancer would …
Deep learning in breast cancer imaging: A decade of progress and future directions
Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
Semantic segmentation of breast cancer images using DenseNet with proposed PSPNet
S Samudrala, CK Mohan - Multimedia Tools and Applications, 2024 - Springer
For early detection of cancer tumors, the semantic segmentation based technique is
proposed because the existing numerous methods fail while classifying due to accuracy and …
proposed because the existing numerous methods fail while classifying due to accuracy and …
Automatic semantic segmentation of breast tumors in ultrasound images based on combining fuzzy logic and deep learning—A feasibility study
SM Badawy, AENA Mohamed, AA Hefnawy, HE Zidan… - PloS one, 2021 - journals.plos.org
Computer aided diagnosis (CAD) of biomedical images assists physicians for a fast
facilitated tissue characterization. A scheme based on combining fuzzy logic (FL) and deep …
facilitated tissue characterization. A scheme based on combining fuzzy logic (FL) and deep …
[HTML][HTML] Application of the convolutional neural networks and supervised deep-learning methods for osteosarcoma bone cancer detection
S Gawade, A Bhansali, K Patil, D Shaikh - Healthcare Analytics, 2023 - Elsevier
Osteosarcoma is a cancerous tumor that occurs in bones. Although it can occur in any bone,
it often occurs in long bones such as arms and legs. The exact cause of this cancerous …
it often occurs in long bones such as arms and legs. The exact cause of this cancerous …
A method for segmentation of tumors in breast ultrasound images using the variant enhanced deep learning
AE Ilesanmi, U Chaumrattanakul… - Biocybernetics and …, 2021 - Elsevier
Background Breast cancer is a deadly disease responsible for statistical yearly global death.
Identification of cancer tumors is quite tasking, as a result, concerted efforts are thus …
Identification of cancer tumors is quite tasking, as a result, concerted efforts are thus …
Semantic segmentation of pancreatic medical images by using convolutional neural network
ML Huang, YZ Wu - Biomedical Signal Processing and Control, 2022 - Elsevier
Pancreatic cancer is the most difficult-to-detect cancer with the highest fatality rate. Pancreas
analysis through abdominal computed tomography (CT) is challenging because the …
analysis through abdominal computed tomography (CT) is challenging because the …
Pre-training in medical data: A survey
Medical data refers to health-related information associated with regular patient care or as
part of a clinical trial program. There are many categories of such data, such as clinical …
part of a clinical trial program. There are many categories of such data, such as clinical …
Boundary-guided and region-aware network with global scale-adaptive for accurate segmentation of breast tumors in ultrasound images
Breast ultrasound (BUS) image segmentation is a critical procedure in the diagnosis and
quantitative analysis of breast cancer. Most existing methods for BUS image segmentation …
quantitative analysis of breast cancer. Most existing methods for BUS image segmentation …
MCRNet: Multi-level context refinement network for semantic segmentation in breast ultrasound imaging
Automated semantic segmentation in breast ultrasound imaging remains a challenging task
due to the adverse impacts of poor contrast, indistinct target boundaries, and a large number …
due to the adverse impacts of poor contrast, indistinct target boundaries, and a large number …