CLEAR: Colon Segmentation with Liquid Error Avoidance and Refinement for VR Colonography

Colon cancer remains a leading cause of cancer-related deaths, emphasizing the importance of early detection and accurate diagnostics. While colonoscopy is the gold standard, its invasiveness deters frequent, widespread use. Desktop colonography offers a less invasive alternative, and Immersive Colonography improves the efficiency of the analysis. However, colonography requires anatomical reconstruction from CTs, and liquid pockets in CT colonography often obscure the colon, necessitating dual-position scans and doubling radiation exposure. We introduce an automatic segmentation method that integrates liquid regions to eliminate the need for a second CT scan. By requiring only one CT image, this approach enhances patient safety and comfort while maintaining accurate segmentation. The proposed method uses advanced filtering and geometry-based techniques to accurately segment air and liquid pockets, ensuring continuity in colon reconstructions. This innovation promises safer, more efficient VR colonography and improved diagnostic capabilities.

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Publication Details

Published
2025-03-08
DOI
https://doi.org/10.1109/vrw66409.2025.00209
Primary Topic
Colorectal Cancer Screening and Detection
Type
article
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article

CLEAR: Colon Segmentation with Liquid Error Avoidance and Refinement for VR Colonography

João Pereira, Catarina Moreira, Anderson Maciel, Joaquim Jorge et al.
Colorectal Cancer Screening and Detection
article

CLEAR: Colon Segmentation with Liquid Error Avoidance and Refinement for VR Colonography

João Pereira, Catarina Moreira, Anderson Maciel, Joaquim Jorge, Pedro J. Freire
article en

Abstract

Colon cancer remains a leading cause of cancer-related deaths, emphasizing the importance of early detection and accurate diagnostics. While colonoscopy is the gold standard, its invasiveness deters frequent, widespread use. Desktop colonography offers a less invasive alternative, and Immersive Colonography improves the efficiency of the analysis. However, colonography requires anatomical reconstruction from CTs, and liquid pockets in CT colonography often obscure the colon, necessitating dual-position scans and doubling radiation exposure. We introduce an automatic segmentation method that integrates liquid regions to eliminate the need for a second CT scan. By requiring only one CT image, this approach enhances patient safety and comfort while maintaining accurate segmentation. The proposed method uses advanced filtering and geometry-based techniques to accurately segment air and liquid pockets, ensuring continuity in colon reconstructions. This innovation promises safer, more efficient VR colonography and improved diagnostic capabilities.

Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento (PT), University of Lisbon (PT), ATA Engineering (United States) (US)
Openalex Percentile: Top 87%
Colorectal Cancer Screening and Detection
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