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15篇 您的检索式:作者名="Merhof"
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1Quest for the best endoscopic imaging modality for computer-assisted colonic polyp staging显示文摘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 staging.AIM To assess which endoscopic imaging modalities are best suited for the computerassisted staging of colonic polyps.METHODS 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 diagnosis.RESULTS 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 of up to 97.4% for one database and up to 84% for the other were achieved. Non-neoplastic lesions were classified more accurately in general than non-neoplastic lesions. It was shown that the image recording conditions highly affect the performance of automated diagnosis systems and partly contribute to a stronger effect on the staging results than the used imaging modality.CONCLUSION Chromoendoscopy has a negative impact on the results of the methods. NBI is better suited than chromoendoscopy. High-definition and high-magnification endoscopy are equally suited.Georg Wimmer Michael Gadermayr Gernot Wolkersdorfer Roland Kwitt Toru Tamaki Jens Tischendorf Michael Hafner Shigeto Yoshida Shinji Tanaka Dorit Merhof Andreas Uhl 2019World Journal of Gastroenterology2019,25,10:2
2Intraoperative visualization of the corticospinal tract by diffusion-tensor-imaging-based fiber tracking 显示文摘Nimsky C Ganslandt O Merhof D 2006Neuroimage2006,30,4:1
3Intraoperative visualization of the pyramidal tract by diffusion-tensorimaging-based fiber tracking 显示文摘Nimsky C Ganslandt O Merhof D 2006Neuroimage2006,30,:1
4Intraoperative visuali-zation of the pyramidal tract by diffusion-tensor-imaging-basedfiber tracking显示文摘Nimsky C Ganslandt O Merhof D 2006Neuroimage2006,30,4:1
5Intraoperative visualization of the pyramidal tract by diffusiontensor-imaging-based fiber wacking显示文摘NIMSKY C GANSLANDT O MERHOF D 2006Neuroimage2006,30,4:1
6Synthesis of 1-deoxy-4-thio-D-ribose starting from thiophene-2-carboxylic acid 显示文摘Altenbach H Brauer D J Merhof G F 1997Tetrahedron1997,53,:1
7Intraoperative visual-ization of the pyramidal tract bydiffusion-tensor-imaging-based fiber tracking显示文摘Nimsky C Ganslandt O Merhof D 0,,04:1
8Anisotropic quadrilateral mesh generation: an indirect approach 显示文摘Merhof D Grosso R Tremel U 2007Engineering Computational Technology2007,38,1112:1
9Hybrid visualization forwhite matter tracts using triangle strips and point sprites显示文摘Merhof D Sonntag M Enders F 2006IEEE Transactions on Visualization and Computer Graphics2006,12,5:1
10Intraoperative visualization of the pyra-midal tract by diffusion tensor imaging based fiber tracking显示文摘Nimsky C Ganslandt O Merhof D 0,,04:1
11Intraoperative visualization of the pyramidal tract by diffusion-tensor-imaging-based fiber tracking显示文摘Nimsky C Ganslandt O Merhof D 2006Neuro Image2006,30,:1
12Intraoperative visualization of the pyramidal tract by diffusion-tensor-imaging-based fiber tracking显示文摘Nimsky C Ganslandt O Merhof D 2006Neuroimage2006,30,4:1
13Evaluation of a human neurite growth assay as specific screen for developmental neurotoxicants显示文摘Krug AK Balmer NV Matt F Sch?nenberger F Merhof D Leist M 2013Arch Toxicol2013,87,12:1
14Anisotropicquadrilateral mesh generation: An indirect approaeh显示文摘MERHOF D GROSSO R TREMEL U 2007Advances in Engineering Software2007,38,:1
15Computer-aided texture analysis combined with experts' knowledge: Improving endoscopic celiac disease diagnosis显示文摘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 settings.RESULTS: 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.Michael Gadermayr Hubert Kogler Maximilian Karla Dorit Merhof Andreas Uhl Andreas Vécsei 2016World Journal of Gastroenterology2016,22,31:1
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