Titlebook: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011; 14th International C Gabor Fichtinger,Anne Martel,Terry Peters Co

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書目名稱Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011影響因子(影響力)




書目名稱Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011影響因子(影響力)學科排名




書目名稱Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011網(wǎng)絡公開度




書目名稱Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011網(wǎng)絡公開度學科排名




書目名稱Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011被引頻次




書目名稱Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011被引頻次學科排名




書目名稱Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011年度引用




書目名稱Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011年度引用學科排名




書目名稱Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011讀者反饋




書目名稱Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011讀者反饋學科排名

Optic-Disk

觀點

Aggregated Distance Metric Learning (ADM) for Image Classification in Presence of Limited Training Draining sets are then combined for image classification. We present a theoretical proof of the superiority of classification by ADM over BDM. Using both clinical (X-ray) and non-clinical (toy car) images in our experiments (with altogether 10 sets of different parameters) and image classification ac

抗體

Jocose

Robust Large Scale Prone-Supine Polyp Matching Using Local Features: A Metric Learning Approachcollapsed segmentation cases. Our automatic approach is extensively evaluated using a large multi-site dataset of 195 patient cases in training and 223 cases for testing. No external examination on the correctness of colon segmentation topology [2] is needed. The results show that we achieve signifi

馬具

Targeted Optical Biopsies for Surveillance Endoscopiesndoscopy into several scenes and establishing cluster correspondences accross these videos. During the second run surveillance (.), the scene recognition is performed in . and . based on the cluster correspondences. Detailed experimental results demonstrate the feasibility of the proposed approach w

載貨清單

Focal Biologically Inspired Feature for Glaucoma Type Classificationd 84.3% images from angle closure glaucoma. The accuracy could be improved close to 90% with more images included in the training. The results show that the focal biologically inspired feature is effective for automatic glaucoma type classification. It can be used to reduce workload of ophthalmologi

抱怨

Assessment of Regional Myocardial Function via Statistical Features in MR Imagesthe most descriptive. Then a Linear Support Vector Machine (SVM) classifier is employed for each of the regional myocardial segments to automatically detect abnormally contracting regions of the myocardium. Based on a clinical dataset of 30 subjects, the evaluation demonstrates that the proposed met

令人作嘔

Simultaneous Segmentation and Grading of Hippocampus for Patient Classification with Alzheimer’s Disuccess rate of 89%. Finally, a comparison of several biomarkers was investigated using a linear discriminant analysis. Conclusion: Using the volume and the grade of the HC at the same time resulted in an efficient patient classification with a success rate of 90%.

mettlesome

Mariam Afshin,Ismail Ben Ayed,Kumaradevan Punithakumar,Max W. K. Law,Ali Islam,Aashish Goela,Ian Rosent survey of the relevant technologies and environment, and will be of benefit to AI researchers engaged with interface design, and practitioners in the area of cultural heritage support and marketing..978-3-642-08824-7978-3-540-68755-9Series ISSN 1611-2482 Series E-ISSN 2197-6635