Lesion Localization in Digital Breast Tomosynthesis with Deformable Transformers by Using 2.5D Information

• In this study, we adapted a transformer-based method to localize lesions in digital breast tomosynthesis (DBT) images. Compared with convolutional neural network-based object detection methods, the transformer-based method does not require non-maximum suppression postprocessing. Integrated deformable convolution detection transformers can better capture small-size lesions. We added transfer learning to tackle the issue of the lack of annotated data from DBT. To validate the superiority of the transformer-based detection method, we compared the results with deep-learning object detection methods. The experimental results demonstrated that the proposed method performs better than all comparison methods.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)

Nyckelord

Deformable Transformers

Digital Breast Tomosynthesis

Lesion Localization

Publikations- och innehållstyp

ref (ämneskategori)

kon (ämneskategori)