Titlebook: Bildverarbeitung für die Medizin 2021; Proceedings, German Christoph Palm,Thomas M. Deserno,Thomas Tolxdorff Conference proceedings 2021 D

独裁者

书目名称Bildverarbeitung für die Medizin 2021影响因子(影响力)




书目名称Bildverarbeitung für die Medizin 2021影响因子(影响力)学科排名




书目名称Bildverarbeitung für die Medizin 2021网络公开度




书目名称Bildverarbeitung für die Medizin 2021网络公开度学科排名




书目名称Bildverarbeitung für die Medizin 2021被引频次




书目名称Bildverarbeitung für die Medizin 2021被引频次学科排名




书目名称Bildverarbeitung für die Medizin 2021年度引用




书目名称Bildverarbeitung für die Medizin 2021年度引用学科排名




书目名称Bildverarbeitung für die Medizin 2021读者反馈




书目名称Bildverarbeitung für die Medizin 2021读者反馈学科排名

AXIS

condescend

An Optical Colon Contour Tracking System for Robot-aided Colonoscopy,ment of balloon after touching the intestine wall is calculated as a vector between the circle‘s center and the image center. This ensures that the robot - aided endoscope can follow the intestinal contour.

Calibrate

Franz-Josef Hutter,Anja Mihr,Carsten Tessmerr 60; 000 annotated landmarks. The proposed heatmap-based neural network achieves a mean positive predictive value (PPV) of 66:68 . 4:67% and a mean true positive rate (TPR) of 24:45 . 5:06% on the intraoperative test dataset and a mean PPV of 81:50 . 5:77% and a mean TPR of 61:60 . 6:11% on a datas

高调

,«Reisen bildet»… Vorurteile und Klischees?,rectional convolutional long short term memory (CONVLSTM), and fusion of bi-directional CONVLSTM and 3D CNNwere trained and tested. The combination of CONVLSTM and 3D CNN surpasses the other two methods and achieves a macro f1-score (mean f1-scores of two classes) of 93%.

圆锥体

ZEST

哥哥喷涌而出

Interactive Design of Convolutional Neural Networks for Medical Image Analysis,ation, and identification. The design of a CNN model traditionally relies on the pre-annotation of a large dataset, the choice of the model‘s architecture, and the tunning of the training hyperparameters. These models are sought as “ black-boxes”, implying that one cannot explain their decisions.

自由职业者

Learning-based Patch-wise Metal Segmentation with Consistency Check,duction (MAR) methods, whose first step is always a segmentation of the present metal objects, try to remove these artifacts. Thereby, the segmentation is a crucial task which has strong influence on the MAR‘s outcome. This study proposes and evaluates a learning-based patch-wise segmentation networ

殖民地