ClickSAM: fine-tuning Segment Anything Model using click prompts for ultrasound image segmentation

Aimee Guo; Grace Fei; Hemanth Pasupuleti; Jing Wang

doi:10.1117/12.3005879

1 April 2024 ClickSAM: fine-tuning Segment Anything Model using click prompts for ultrasound image segmentation

Aimee Guo, Grace Fei, Hemanth Pasupuleti, Jing Wang

Proceedings Volume 12932, Medical Imaging 2024: Ultrasonic Imaging and Tomography; 1293212 (2024) https://doi.org/10.1117/12.3005879
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Conference Poster

Abstract

The newly released Segment Anything Model (SAM) is a popular tool used in image processing due to its superior segmentation accuracy, variety of input prompts, training capabilities, and efficient model design. However, its current model is trained on a diverse dataset not tailored to medical images, particularly ultrasound images. Ultrasound images tend to have a lot of noise, making it difficult to segment out important structures. In this project, we developed ClickSAM, which fine-tunes the Segment Anything Model using click prompts for ultrasound images. ClickSAM has two stages of training: the first stage is trained on single-click prompts centered in the ground-truth contours, and the second stage focuses on improving the model performance through additional positive and negative click prompts. By comparing the first stage’s predictions to the ground-truth masks, true positive, false positive, and false negative segments are calculated. Positive clicks are generated using the true positive and false negative segments, and negative clicks are generated using the false positive segments. The Centroidal Voronoi Tessellation algorithm is then employed to collect positive and negative click prompts in each segment that are used to enhance the model performance during the second stage of training. With click-train methods, ClickSAM exhibits superior performance compared to other existing models for ultrasound image segmentation.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Aimee Guo, Grace Fei, Hemanth Pasupuleti, and Jing Wang "ClickSAM: fine-tuning Segment Anything Model using click prompts for ultrasound image segmentation", Proc. SPIE 12932, Medical Imaging 2024: Ultrasonic Imaging and Tomography, 1293212 (1 April 2024); https://doi.org/10.1117/12.3005879

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