کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
3302650 1210301 2016 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Computer-aided diagnosis of colorectal polyp histology by using a real-time image recognition system and narrow-band imaging magnifying colonoscopy
ترجمه فارسی عنوان
تشخیص به کمک کامپیوتر بافت شناسی پولیپ کولورکتال با استفاده از یک سیستم تشخیص تصویر زمان واقعی و کولونوسکوپی بزرگنمایی تصویربرداری باند باریک
کلمات کلیدی
NBI، تصویربرداری با باند باریک؛ NPV، ارزش پیش بینی منفی؛ PIVI، حفظ و اختلاط نوآوری های ارزشمند تشخیصی؛ PPV، ارزش پیش بینی مثبت؛ ROI، منطقه مورد علاقه؛ SIFT، پشتیبانی ماشین بردار
موضوعات مرتبط
علوم پزشکی و سلامت پزشکی و دندانپزشکی بیماری‌های گوارشی
چکیده انگلیسی

Background and AimsIt is necessary to establish cost-effective examinations and treatments for diminutive colorectal tumors that consider the treatment risk and surveillance interval after treatment. The Preservation and Incorporation of Valuable Endoscopic Innovations (PIVI) committee of the American Society for Gastrointestinal Endoscopy published a statement recommending the establishment of endoscopic techniques that practice the resect and discard strategy. The aims of this study were to evaluate whether our newly developed real-time image recognition system can predict histologic diagnoses of colorectal lesions depicted on narrow-band imaging and to satisfy some problems with the PIVI recommendations.MethodsWe enrolled 41 patients who had undergone endoscopic resection of 118 colorectal lesions (45 nonneoplastic lesions and 73 neoplastic lesions). We compared the results of real-time image recognition system analysis with that of narrow-band imaging diagnosis and evaluated the correlation between image analysis and the pathological results.ResultsConcordance between the endoscopic diagnosis and diagnosis by a real-time image recognition system with a support vector machine output value was 97.5% (115/118). Accuracy between the histologic findings of diminutive colorectal lesions (polyps) and diagnosis by a real-time image recognition system with a support vector machine output value was 93.2% (sensitivity, 93.0%; specificity, 93.3%; positive predictive value (PPV), 93.0%; and negative predictive value, 93.3%).ConclusionsAlthough further investigation is necessary to establish our computer-aided diagnosis system, this real-time image recognition system may satisfy the PIVI recommendations and be useful for predicting the histology of colorectal tumors.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Gastrointestinal Endoscopy - Volume 83, Issue 3, March 2016, Pages 643–649
نویسندگان
, , , , , , , , , ,