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

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.

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 The Efficacy of Linked Color Imaging in the Endoscopic Diagnosis of Barrett’s Esophagus and Esophageal Adenocarcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Mamoru Tokunaga ◽  
Tomoaki Matsumura ◽  
Kentaro Ishikawa ◽  
Tatsuya Kaneko ◽  
Hirotaka Oura ◽  
...  
Keyword(s):  
Barrett’S Esophagus ◽  
Esophageal Adenocarcinoma ◽  
Barrett's Esophagus ◽  
Color Space ◽  
Color Difference ◽  
Blue Laser ◽  
Color Imaging ◽  
Color Differences ◽  
Blue Laser Imaging ◽  
Linked Color Imaging

Background. The present study aimed to evaluate the efficacy of linked color imaging (LCI) in diagnosing Barrett’s esophagus (BE) and esophageal adenocarcinoma (EAC). Methods. A total of 112 and 12 consecutive patients with BE and EAC were analyzed. The visibility scores of BE and EAC ranging from 4 (excellent visibility) to 0 (not detectable) were evaluated by three trainees and three experts using white light imaging (WLI), LCI mode, and blue laser imaging bright (BLI-b) mode. In addition, L ∗ a ∗ b ∗ color values and color differences ( Δ E ∗ ) were evaluated using the CIELAB color space system. Results. The visibility score of the BE in LCI mode ( 2.94 ± 1.32 ) was significantly higher than those in WLI ( 2.46 ± 1.48 ) and BLI-b mode ( 2.35 ± 1.46 ) ( p < 0.01 ). The color difference ( Δ E ∗ ) from the adjacent gastric mucosa in LCI mode ( 17.11 ± 8.53 ) was significantly higher than those in other modes ( 12.52 ± 9.37 in WLI and 11.96 ± 6.59 in BLI-b mode, p < 0.01 ). The visibility scores of EAC in LCI mode ( 2.56 ± 1.47 ) and BLI-b mode ( 2.51 ± 1.28 ) were significantly higher than that in WLI ( 1.64 ± 1.46 ) ( p < 0.01 ). The color difference ( Δ E ∗ ) from the adjacent normal Barrett’s mucosa in LCI mode ( 19.96 ± 7.97 ) was significantly higher than that in WLI ( 12.95 ± 11.86 ) ( p = 0.03 ). Conclusion. The present findings suggest that LCI increases the visibility of BE and EAC and contributes to the improvement of the detection of these lesions.

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 Linked color imaging (LCI), a novel image-enhanced endoscopy technology, emphasizes the color of early gastric cancer

2017 ◽  
Vol 05 (10) ◽  
pp. E1005-E1013 ◽  
Author(s):  
Hiromitsu Kanzaki ◽  
Ryuta Takenaka ◽  
Yoshiro Kawahara ◽  
Daisuke Kawai ◽  
Yuka Obayashi ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Early Gastric Cancer ◽  
Color Space ◽  
Region Of Interest ◽  
Color Difference ◽  
Blue Laser ◽  
Color Imaging ◽  
Blue Laser Imaging ◽  
Color Value ◽  
Linked Color Imaging

Abstract Background and study aims Linked color imaging (LCI) and blue laser imaging (BLI) are novel image-enhanced endoscopy technologies with strong, unique color enhancement. We investigated the efficacy of LCI and BLI-bright compared to conventional white light imaging (WLI) by measuring the color difference between early gastric cancer lesions and the surrounding mucosa. Patients and methods Images of early gastric cancer scheduled for endoscopic submucosal dissection were captured by LCI, BLI-bright, and WLI under the same conditions. Color values of the lesion and surrounding mucosa were defined as the average of the color value in each region of interest. Color differences between the lesion and surrounding mucosa (ΔE) were examined in each mode. The color value was assessed using the CIE L*a*b* color space (CIE: Commission Internationale d’Eclairage). Results We collected images of 43 lesions from 42 patients. Average ΔE values with LCI, BLI-bright, and WLI were 11.02, 5.04, and 5.99, respectively. The ΔE was significantly higher with LCI than with WLI (P < 0.001). Limited to cases of small ΔE with WLI, the ΔE was approximately 3 times higher with LCI than with WLI (7.18 vs. 2.25). The ΔE with LCI was larger when the surrounding mucosa had severe intestinal metaplasia (P = 0.04). The average color value of a lesion and the surrounding mucosa differed. This value did not have a sufficient cut-off point between the lesion and surrounding mucosa to distinguish them, even with LCI. Conclusion LCI had a larger ΔE than WLI. It may allow easy recognition and early detection of gastric cancer, even for inexperienced endoscopists.

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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