|Title:||Computer-aided diagnosis for identifying and delineating early gastric cancers in magnifying narrow-band imaging||Authors:||Kanesaka T.
|Issue Date:||2018||Publisher:||Mosby Inc.||Journal Volume:||87||Journal Issue:||5||Start page/Pages:||1339-1344||Source:||Gastrointestinal Endoscopy||Abstract:||
Background and Aims: Magnifying narrow-band imaging (M-NBI) is important in the diagnosis of early gastric cancers (EGCs) but requires expertise to master. We developed a computer-aided diagnosis (CADx) system to assist endoscopists in identifying and delineating EGCs. Methods: We retrospectively collected and randomly selected 66 EGC M-NBI images and 60 non-cancer M-NBI images into a training set and 61 EGC M-NBI images and 20 non-cancer M-NBI images into a test set. After preprocessing and partition, we determined 8 gray-level co-occurrence matrix (GLCM) features for each partitioned 40 × 40 pixel block and calculated a coefficient of variation of 8 GLCM feature vectors. We then trained a support vector machine (SVMLv1) based on variation vectors from the training set and examined in the test set. Furthermore, we collected 2 determined P and Q GLCM feature vectors from cancerous image blocks containing irregular microvessels from the training set, and we trained another SVM (SVMLv2) to delineate cancerous blocks, which were compared with expert-delineated areas for area concordance. Results: The diagnostic performance revealed accuracy of 96.3%, precision (positive predictive value [PPV]) of 98.3%, recall (sensitivity) of 96.7%, and specificity of 95%, at a rate of 0.41 ± 0.01 seconds per image. The performance of area concordance, on a block basis, demonstrated accuracy of 73.8% ± 10.9%, precision (PPV) of 75.3% ± 20.9%, recall (sensitivity) of 65.5% ± 19.9%, and specificity of 80.8% ± 17.1%, at a rate of 0.49 ± 0.04 seconds per image. Conclusions: This pilot study demonstrates that our CADx system has great potential in real-time diagnosis and delineation of EGCs in M-NBI images. ? 2018
|ISSN:||0016-5107||DOI:||10.1016/j.gie.2017.11.029||SDG/Keyword:||aged; Article; cancer diagnosis; clinical evaluation; computer assisted diagnosis; diagnostic accuracy; diagnostic test accuracy study; early cancer; early gastric cancer; endoscopic submucosal dissection; endoscopist; endoscopy; female; histogram; human; image processing; image quality; magnifying narrow band imaging; major clinical study; male; microvasculature; narrow band imaging; predictive value; priority journal; retrospective study; sensitivity and specificity; stomach cancer; support vector machine; case control study; computer assisted diagnosis; diagnostic imaging; early cancer diagnosis; gastroscopy; middle aged; narrow band imaging; pilot study; procedures; stomach tumor; Aged; Case-Control Studies; Diagnosis, Computer-Assisted; Early Detection of Cancer; Female; Gastroscopy; Humans; Image Processing, Computer-Assisted; Male; Middle Aged; Narrow Band Imaging; Pilot Projects; Predictive Value of Tests; Retrospective Studies; Sensitivity and Specificity; Stomach Neoplasms
|Appears in Collections:||醫學系|
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