Metal Contamination Behavior on Silicon Dioxide Surface Rinsed With Deionized Water Containing Ultra-Trace Metal During Single-Wafer Cleaning
Colonoscopy is considered the gold standard for detecting and diagnosing colorectal cancer (CRC), which is the second most common cause of cancer-related deaths worldwide. While colonoscopy is generally safe and effective at reducing CRC mortality, lesions can be missed during procedures, with adverse impacts on the patient. Latest innovations in hardware and software led to the development of adjunct tools for complementing standard colonoscopy to ensure optimal outcomes. Such tools aim to enhance the detection of lesions, standardize procedures, enhance safety, and minimize discomfort. Ultimately, they contribute to reducing the morbidity and mortality rates associated with CRC. This survey comprehensively explores both clinically tested and emerging advanced hardware and software adjunct tools, categorizing them based on their role in targeting three clinical challenges: mucosal visualization, lesion detection and classification, and navigation and procedure assessment. Moreover, this analysis allows exploring synergistic strategies for the future of the practice, with a focus on the promising role of AI-embedded robotic technologies.
Authors
- Takezo Mawaki (ORCID: https://orcid.org/0000-0003-2266-6092)
- Yasuyuki Shirai (ORCID: https://orcid.org/0000-0002-8211-7733)
- Kyohei Tsutano
- Rihito Kuroda (ORCID: https://orcid.org/0000-0001-7812-3084)
Institutions
- Tohoku University (JP)
- National Sagamihara Hospital (JP)
- Organ Technologies (Japan) (JP)
Publication Details
- Journal
- IEEE Transactions on Semiconductor Manufacturing
- Published
- 2025-06-02
- DOI
- https://doi.org/10.1109/tsm.2025.3575743
- Primary Topic
- Industrial Vision Systems and Defect Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00