UTILIZING MULTI-VIEW CHEST X-RAY 3D RECONSTRUCTION TO IMPROVE THORAX DISEASE DIAGNISIS

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Published Jun 5, 2025
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Vol. 10 No. 1 (2025): Volume 10 Issue 1

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Mr. Birudev Yele
Faculty of Science and Technology, School of Computational Sciences JSPM UNIVERSITY, Wagholi, Pune 412207, Maharashtra, India
Dr. Waseem Mir
Faculty of Science and Technology, School of Computational Sciences JSPM UNIVERSITY, Wagholi, Pune 412207, Maharashtra, India

Abstract

In patient management and treatment planning, precise diagnosis of thorax diseases is of prime significance. Although Chest X-rays (CXR) are a widely used modality for this, their two-dimensional, flat representation has limitations in evaluating complex anatomical structures. By utilizing multi-view 3D reconstruction from Chest X-rays, one is able to gain a better overview of the thorax, potentially improving the detection of diseases. Our work is aimed at investigating the application of Medical Neural Radiance Fields (MedNeRF), an approach using neural radiance fields, for this and demonstrates its capability to accurately reconstruct the thorax from multiple X-ray images with detailed observations of both skeletal and internal anatomy. The final 3D models match the initial X-ray pictures and are similar to those produced using conventional methods.

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite
[1]
Mr. Birudev Yele and Dr. Waseem Mir, “UTILIZING MULTI-VIEW CHEST X-RAY 3D RECONSTRUCTION TO IMPROVE THORAX DISEASE DIAGNISIS”, IEJRD - International Multidisciplinary Journal, vol. 10, no. 1, p. 17, Jun. 2025.

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