3D reconstruction of gastrointestinal regions using shape-from-focus

Bilal Ahmad; Ivar Farup; Pål Anders Floor

doi:10.1117/12.2679345

7 June 2023 3D reconstruction of gastrointestinal regions using shape-from-focus

Bilal Ahmad, Ivar Farup, Pål Anders Floor

Proceedings Volume 12701, Fifteenth International Conference on Machine Vision (ICMV 2022); 127011J (2023) https://doi.org/10.1117/12.2679345
Event: Fifteenth International Conference on Machine Vision (ICMV 2022), 2022, Rome, Italy

Abstract

3D shape reconstruction from images is an active topic in computer vision. Shape-from-Focus (SFF) is an important approach which requires image stack in a focus controlled manner to infer the 3D shape. In this article, 3D reconstruction of synthetic gastrointestinal regions is done using SFF. Image stack is generated in Blender software with focus controlled camera. A color focus measure is applied for shape recovery followed by a weighted L2 regularizer to estimate for inaccurate depth values. A precise comparison is done between recovered shape and ground truth data by measuring the depth error and correlation between them. Results shows that SFF technique will be practical for 3D reconstruction of GI regions with focus and motion controlled pillcams which is technologically feasible to implement.

Citation Download Citation

Bilal Ahmad, Ivar Farup, and Pål Anders Floor "3D reconstruction of gastrointestinal regions using shape-from-focus", Proc. SPIE 12701, Fifteenth International Conference on Machine Vision (ICMV 2022), 127011J (7 June 2023); https://doi.org/10.1117/12.2679345

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