This study aims to develop a deep learning model architecture for breast cancer mass detection and segmentation using the mammography.

This study aims to develop a deep learning model architecture for breast cancer mass detection and segmentation using the mammography.

This study aims to develop a deep learning model architecture for breast cancer mass detection and segmentation using the mammography.

A double shot model for mass detection and segmentation simultaneously is proposed to use a combination of YOLO and LOGO architectures.

Highlights•Mass detection and segmentation in digital mammograms play a crucial role in early breast cancer detection and treatment. •A double shot model ...

Oct 1, 2024 · Su et al. [9] developed a YOLO-LOGO model for breast mass detection and segmentation in digital mammograms. Their model effectively combined ...

Jun 1, 2022 · The proposed model has a higher efficiency, reduces computational requirements, and improves the versatility and accuracy of computer-aided ...

Firstly, we adopted YoloV5L6, the state-of-the-art object detection model, to position and crop the breast mass in mammograms with a high resolution; Secondly, ...

YOLO-LOGO: A transformer-based YOLO segmentation model for breast mass detection and segmentation in digital mammograms. Link. Content. Introduction ...

Jun 1, 2022 · This study aims to develop a deep learning model architecture for breast cancer mass detection and segmentation using the mammography.In this ...