Anatomical landmark detection in chest x-ray images using transformer-based networks

Akhil Kasturi; Ali Vosoughi; Nathan Hadjiyski; Larry Stockmaster; William J. Sehnert; Axel Wismüller

doi:10.1117/12.3006881

3 April 2024 Anatomical landmark detection in chest x-ray images using transformer-based networks

Akhil Kasturi, Ali Vosoughi, Nathan Hadjiyski, Larry Stockmaster, William J. Sehnert, Axel Wismüller

Proceedings Volume 12927, Medical Imaging 2024: Computer-Aided Diagnosis; 129272Q (2024) https://doi.org/10.1117/12.3006881
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Conference Poster

Abstract

In this work, we utilize a Transformer-based network for precise anatomical landmark detection in chest X-ray images. By combining the strengths of Transformers and UNet architecture, our proposed model achieves robust landmark localization by effectively capturing global context and spatial dependencies. Notably, our method surpasses the current state-of-the-art approaches, exhibiting a significant reduction in Mean Radial Error and a notable improvement in the rate of accurate landmark detection. Each of the landmark points in the labels is presented as a Gaussian heatmap for training the network, using a hybrid loss function, incorporating binary cross-entropy and Dice loss functions, allowing for pixel-wise classification of the heatmaps and segmentation-based training to accurately localize the landmark heatmaps. The promising results obtained highlight the underexplored potential of Transformers in anatomical landmark detection and offer a compelling solution for accurate anatomical landmark detection in chest X-rays. Our work demonstrates the viability of Transformer-based models in addressing the challenges of landmark detection in medical imaging.

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

Citation Download Citation

Akhil Kasturi, Ali Vosoughi, Nathan Hadjiyski, Larry Stockmaster, William J. Sehnert, and Axel Wismüller "Anatomical landmark detection in chest x-ray images using transformer-based networks", Proc. SPIE 12927, Medical Imaging 2024: Computer-Aided Diagnosis, 129272Q (3 April 2024); https://doi.org/10.1117/12.3006881

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