scholarly journals New Diagnostic Approach for Esophageal Squamous Cell Neoplasms Using Linked Color Imaging and Blue Laser Imaging Combined with Iodine Staining

2019 ◽  
Vol 52 (5) ◽  
pp. 497-501 ◽  
Author(s):  
Masato Tsunoda ◽  
Yoshimasa Miura ◽  
Hiroyuki Osawa ◽  
Tsevelnorov Khurelbaatar ◽  
Mio Sakaguchi ◽  
...  
Keyword(s):  
Squamous Cell ◽  
Blue Laser ◽  
Diagnostic Approach ◽  
Laser Imaging ◽  
Color Imaging ◽  
Iodine Staining ◽  
Blue Laser Imaging ◽  
Linked Color Imaging ◽  
Squamous Cell Neoplasms

scholarly journals A CNN CADx System for Multimodal Classification of Colorectal Polyps Combining WL, BLI, and LCI Modalities

2020 ◽  
Vol 10 (15) ◽  
pp. 5040 ◽  
Author(s):  
Roger Fonollà ◽  
Quirine E. W. van der Zander ◽  
Ramon M. Schreuder ◽  
Ad A. M. Masclee ◽  
Erik J. Schoon ◽  
...  
Keyword(s):  
Area Under The Curve ◽  
Colorectal Polyps ◽  
Blue Laser ◽  
Classification Model ◽  
Misclassification Rate ◽  
Laser Imaging ◽  
Color Imaging ◽  
Additional Information ◽  
Blue Laser Imaging ◽  
Linked Color Imaging

Colorectal polyps are critical indicators of colorectal cancer (CRC). Blue Laser Imaging and Linked Color Imaging are two modalities that allow improved visualization of the colon. In conjunction with the Blue Laser Imaging (BLI) Adenoma Serrated International Classification (BASIC) classification, endoscopists are capable of distinguishing benign and pre-malignant polyps. Despite these advancements, this classification still prevails a high misclassification rate for pre-malignant colorectal polyps. This work proposes a computer aided diagnosis (CADx) system that exploits the additional information contained in two novel imaging modalities, enabling more informative decision-making during colonoscopy. We train and benchmark six commonly used CNN architectures and compare the results with 19 endoscopists that employed the standard clinical classification model (BASIC). The proposed CADx system for classifying colorectal polyps achieves an area under the curve (AUC) of 0.97. Furthermore, we incorporate visual explanatory information together with a probability score, jointly computed from White Light, Blue Laser Imaging, and Linked Color Imaging. Our CADx system for automatic polyp malignancy classification facilitates future advances towards patient safety and may reduce time-consuming and costly histology assessment.

Blue laser imaging and linked color imaging improve the color difference value and visibility of colorectal polyps in underwater conditions

2020 ◽  
Vol 32 (5) ◽  
pp. 791-800 ◽  
Author(s):  
Yasushi Yamasaki ◽  
Keita Harada ◽  
Shumpei Yamamoto ◽  
Eriko Yasutomi ◽  
Shotaro Okanoue ◽  
...  
Keyword(s):  
Color Difference ◽  
Colorectal Polyps ◽  
Blue Laser ◽  
Laser Imaging ◽  
Color Imaging ◽  
Blue Laser Imaging ◽  
Linked Color Imaging

Comparison Between Linked Color Imaging and Blue Laser Imaging for Improving the Visibility of Flat Colorectal Polyps: A Multicenter Pilot Study

2019 ◽  
Vol 65 (7) ◽  
pp. 2054-2062
Author(s):  
Naohisa Yoshida ◽  
Takashi Hisabe ◽  
Hiroaki Ikematsu ◽  
Hiroshi Ishihara ◽  
Masaki Terasawa ◽  
...  
Keyword(s):  
Pilot Study ◽  
Colorectal Polyps ◽  
Blue Laser ◽  
Laser Imaging ◽  
Color Imaging ◽  
Blue Laser Imaging ◽  
Linked Color Imaging

scholarly journals Linked Color Imaging and Blue Laser Imaging for Upper Gastrointestinal Screening

2018 ◽  
Vol 51 (6) ◽  
pp. 513-526 ◽  
Author(s):  
Hiroyuki Osawa ◽  
Yoshimasa Miura ◽  
Takahito Takezawa ◽  
Yuji Ino ◽  
Tsevelnorov Khurelbaatar ◽  
...  
Keyword(s):  
Blue Laser ◽  
Laser Imaging ◽  
Color Imaging ◽  
Blue Laser Imaging ◽  
Linked Color Imaging ◽  
Upper Gastrointestinal

scholarly journals Blue Laser Imaging, Blue Light Imaging, and Linked Color Imaging for the Detection and Characterization of Colorectal Tumors

Gut and Liver ◽  
2019 ◽  
Vol 13 (2) ◽  
pp. 140-148 ◽  
Author(s):  
Naohisa Yoshida ◽  
Osamu Dohi ◽  
Ken Inoue ◽  
Ritsu Yasuda ◽  
Takaaki Murakami ◽  
...  
Keyword(s):  
Blue Light ◽  
Blue Laser ◽  
Colorectal Tumors ◽  
Laser Imaging ◽  
Color Imaging ◽  
Blue Laser Imaging ◽  
Linked Color Imaging

scholarly journals Mo1632 IMPROVEMENT OF POLYP DETECTION USING ARTIFICIAL INTELLIGENCE WITH BLUE LASER IMAGING AND LINKED COLOR IMAGING

2020 ◽  
Vol 91 (6) ◽  
pp. AB428
Author(s):  
Satoshi Sugino ◽  
Naohisa Yoshida ◽  
Xin Zhu ◽  
Ken Inoue ◽  
Ritsu Yasuda ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Blue Laser ◽  
Polyp Detection ◽  
Laser Imaging ◽  
Color Imaging ◽  
Blue Laser Imaging ◽  
Linked Color Imaging
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