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Computer-aided texture analysis combined with experts' knowledge: Improving endoscopic celiac disease diagnosis

World Journal of Gastroenterology 2016年第31期22卷 7124-7134页

作者： Michael Gadermayr Hubert Kogler Maximilian Karla Dorit Merhof andreas uhl andreas Vécsei Institute of Imaging and Computer Vision RWTH Aachen University Department of Pediatrics Pediatric Gastroenterology St Anna Children’s Hospital Medical University Vienna Department of Computer Sciences University of Salzburg

AIM: To further improve the endoscopic detection of intestinal mucosa alterations due to celiac disease(CD).METHODS: We assessed a hybrid approach based on the integration of expert knowledge into the computerbased classification pipeline. A total of 2835 endoscopic images from the duodenum were recorded in 290 children using the modified immersion technique(MIT). These children underwent routine upper endoscopy for suspected CD or non-celiac upper abdominal symptoms between August 2008 and December 2014. Blinded to the clinical data and biopsy results, three medical experts visually classified each image as normal mucosa(Marsh-0) or villous atrophy(Marsh-3). The experts' decisions were further integrated into state-of-the-arttexture recognition systems. Using the biopsy results as the reference standard, the classification accuracies of this hybrid approach were compared to the experts' diagnoses in 27 different ***: Compared to the experts' diagnoses, in 24 of 27 classification settings(consisting of three imaging modalities, three endoscopists and three classification approaches), the best overall classification accuracies were obtained with the new hybrid approach. In 17 of 24 classification settings, the improvements achieved with the hybrid approach were statistically significant(P < 0.05). Using the hybrid approach classification accuracies between 94% and 100% were obtained. Whereas the improvements are only moderate in the case of the most experienced expert, the results of the less experienced expert could be improved significantly in 17 out of 18 classification settings. Furthermore, the lowest classification accuracy, based on the combination of one database and one specific expert, could be improved from 80% to 95%(P < 0.001).CONCLUSION: The overall classification performance of medical experts, especially less experienced experts, can be boosted significantly by integrating expert knowledge into computer-aided diagnosis systems.

关键词： Celiac disease Diagnosis endoscopy Computer-aided texture analysis Biopsy Pattern recognition

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Quest for the best endoscopic imaging modality for computer-assisted colonic polyp staging

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World Journal of Gastroenterology 2019年第10期25卷 1197-1209页

作者： Georg Wimmer Michael Gadermayr Gernot Wolkersdorfer Roland Kwitt Toru Tamaki Jens Tischendorf Michael Hafner Shigeto Yoshida Shinji Tanaka Dorit Merhof andreas uhl Department of Computer Sciences University of Salzburg Interdisciplinary Imaging and Vision Institute Aachen RWTH Aachen Department of Internal Medicine I Paracelsus Medical University/Salzburger Landeskliniken(SALK) Department of Information Engineering Graduate School of EngineeringHiroshima University Internal Medicine and Gastroenterology University Hospital Aachen Department of Gastroenterologie and Hepatologie Krankenhaus St.Elisabeth Department of Endoscopy and Medicine Graduate School of Biomedical and Health ScienceHiroshima University Department of Endoscopy Hiroshima University Hospital

BACKGROUND It was shown in previous studies that high definition endoscopy, high magnification endoscopy and image enhancement technologies, such as chromoendoscopy and digital chromoendoscopy [narrow-band imaging(NBI), iScan] facilitate the detection and classification of colonic polyps during endoscopic sessions. However, there are no comprehensive studies so far that analyze which endoscopic imaging modalities facilitate the automated classification of colonic polyps. In this work, we investigate the impact of endoscopic imaging modalities on the results of computer-assisted diagnosis systems for colonic polyp *** To assess which endoscopic imaging modalities are best suited for the computerassisted staging of colonic *** In our experiments, we apply twelve state-of-the-art feature extraction methods for the classification of colonic polyps to five endoscopic image databases of colonic lesions. For this purpose, we employ a specifically designed experimental setup to avoid biases in the outcomes caused by differing numbers of images per image database. The image databases were obtained using different imaging modalities. Two databases were obtained by high-definition endoscopy in combination with i-Scan technology(one with chromoendoscopy and one without chromoendoscopy). Three databases were obtained by highmagnification endoscopy(two databases using narrow band imaging and one using chromoendoscopy). The lesions are categorized into non-neoplastic and neoplastic according to the histological *** Generally, it is feature-dependent which imaging modalities achieve high results and which do not. For the high-definition image databases, we achieved overall classification rates of up to 79.2% with chromoendoscopy and 88.9% without chromoendoscopy. In the case of the database obtained by high-magnification chromoendoscopy, the classification rates were up to 81.4%. For the combination of high-magnification endoscopy with NBI, results

关键词： Endoscopy Colonic polyps Automated diagnosis system Narrow-band imaging Chromoendoscopy Imaging modalities Image enhancement technologies

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Long-term survival after pancreaticoduodenectomy in patients with ductal adenocarcinoma of the pancreatic head

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Hepatobiliary & Pancreatic Diseases International 2021年第3期20卷 271-278页

作者： andreas Minh Luu Chris Braumann Orlin Belyaev Monika Janot-Matuschek Henrik Rudolf Michael Praktiknjo Waldemar uhl Department of General and Visceral Surgery St.Josef HospitalRuhr University BochumGudrunstrasse 56Bochum 44791Germany Department of Medical Informatics Biometry and EpidemiologyRuhr University BochumUniversitaetsstrasse 105Bochum 44789Germany Department of Internal Medicine University of BonnVenusberg-Campus 1Bonn 53127Germany

Background: Pancreatic ductal adenocarcinoma(PDAC) has the worst prognosis of all malignant tumors due to unavailable screening methods, late diagnosis with a low proportion of resectable tumors and resistance to systemic treatment. Complete tumor resection remains the cornerstone of modern multimodal strategies aiming at long-term survival. This study was performed to investigate the overall rate of long-term survival(LTS) and its contributing factors. Methods: This was a retrospective single-center analysis of consecutive patients undergoing pancreaticoduodenectomy(PD) for PDAC between 2007 and 2014 at the St. Josef Hospital, Ruhr University Bochum, Germany. Clinical and laboratory parameters were assessed and evaluated for prediction of LTS with Cox regression analysis. Results: The overall rate of LTS after PD for PDAC was 20.4%(34/167). Median survival was 24 months regardless of adjuvant treatment. Carbohydrate antigen 19-9 levels, tumor grade, lymph vessel invasion, perineural invasion and reduced general condition were significantly associated with LTS in univariate analysis( P<0.05). Serum levels of carbohydrate antigen 19-9, American Joint Committee on Cancer stage, tumor grade, abdominal pain, male, exocrine pancreatic insufficiency and duration of postoperative hospital stay were independent predictors of cancer survival in multivariable analysis. Conclusions: Cancer related characteristics are associated with LTS in multimodally treated patients after curative PDAC surgery.

关键词： Pancreaticoduodenectomy Whipple’s procedure Pancreatic cancer survival Ductal adenocarcinoma Pancreas Pancreatic surgery

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