A New Dataset and A Baseline Model for Breast Lesion Detection in Ultrasound Videos

by   Zhi Lin, et al.

Breast lesion detection in ultrasound is critical for breast cancer diagnosis. Existing methods mainly rely on individual 2D ultrasound images or combine unlabeled video and labeled 2D images to train models for breast lesion detection. In this paper, we first collect and annotate an ultrasound video dataset (188 videos) for breast lesion detection. Moreover, we propose a clip-level and video-level feature aggregated network (CVA-Net) for addressing breast lesion detection in ultrasound videos by aggregating video-level lesion classification features and clip-level temporal features. The clip-level temporal features encode local temporal information of ordered video frames and global temporal information of shuffled video frames. In our CVA-Net, an inter-video fusion module is devised to fuse local features from original video frames and global features from shuffled video frames, and an intra-video fusion module is devised to learn the temporal information among adjacent video frames. Moreover, we learn video-level features to classify the breast lesions of the original video as benign or malignant lesions to further enhance the final breast lesion detection performance in ultrasound videos. Experimental results on our annotated dataset demonstrate that our CVA-Net clearly outperforms state-of-the-art methods. The corresponding code and dataset are publicly available at <https://github.com/jhl-Det/CVA-Net>.


page 2

page 4

page 7


Semi-supervised Breast Lesion Detection in Ultrasound Video Based on Temporal Coherence

Breast lesion detection in ultrasound video is critical for computer-aid...

A Spatial-Temporal Deformable Attention based Framework for Breast Lesion Detection in Videos

Detecting breast lesion in videos is crucial for computer-aided diagnosi...

Key-frame Guided Network for Thyroid Nodule Recognition using Ultrasound Videos

Ultrasound examination is widely used in the clinical diagnosis of thyro...

Boosting Breast Ultrasound Video Classification by the Guidance of Keyframe Feature Centers

Breast ultrasound videos contain richer information than ultrasound imag...

Enhancing Non-mass Breast Ultrasound Cancer Classification With Knowledge Transfer

Much progress has been made in the deep neural network (DNN) based diagn...

Check and Link: Pairwise Lesion Correspondence Guides Mammogram Mass Detection

Detecting mass in mammogram is significant due to the high occurrence an...

Please sign up or login with your details

Forgot password? Click here to reset