AMS-PAN: Breast ultrasound image segmentation model combining attention mechanism and multi-scale features

Cancer statistics, 2022

(2022) Rebecca L. Siegel et al.   CA-A CANCER JOURNAL FOR CLINICIANS

GFNet: Automatic segmentation of COVID-19 lung infection regions using CT images based on boundary features

(2022) Chaodong Fan et al.   PATTERN RECOGNITION

AAU-Net: An Adaptive Attention U-Net for Breast Lesions Segmentation in Ultrasound Images

(2022) Gongping Chen et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Global guidance network for breast lesion segmentation in ultrasound images

(2021) Cheng Xue et al.   MEDICAL IMAGE ANALYSIS

Accurate segmentation of breast tumors using AE U-net with HDC model in ultrasound images

(2021) Yu Yan et al.   Biomedical Signal Processing and Control

Breast mass segmentation in ultrasound with selective kernel U-Net convolutional neural network

(2020) Michal Byra et al.   Biomedical Signal Processing and Control

Self-co-attention neural network for anatomy segmentation in whole breast ultrasound

(2020) Baiying Lei et al.   MEDICAL IMAGE ANALYSIS

Salient Object Detection Combining a Self-Attention Module and a Feature Pyramid Network

(2020) Guangyu Ren et al.   Electronics

DUNet: A deformable network for retinal vessel segmentation

(2019) Qiangguo Jin et al.   KNOWLEDGE-BASED SYSTEMS

An RDAU-NET model for lesion segmentation in breast ultrasound images

(2019) Zhemin Zhuang et al.   PLoS One

An improved random forest-based rule extraction method for breast cancer diagnosis

(2019) Sutong Wang et al.   APPLIED SOFT COMPUTING

UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation

(2019) Zongwei Zhou et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks

(2018) Moi Hoon Yap et al.   IEEE Journal of Biomedical and Health Informatics

Open access database of raw ultrasonic signals acquired from malignant and benign breast lesions

(2017) Hanna Piotrzkowska-Wróblewska et al.   MEDICAL PHYSICS