Titlebook: Information Processing in Medical Imaging; 22nd International C Gábor Székely,Horst K. Hahn Conference proceedings 2011 Springer-Verlag Gmb

Garfield

書目名稱Information Processing in Medical Imaging影響因子(影響力)




書目名稱Information Processing in Medical Imaging影響因子(影響力)學(xué)科排名




書目名稱Information Processing in Medical Imaging網(wǎng)絡(luò)公開度




書目名稱Information Processing in Medical Imaging網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Information Processing in Medical Imaging被引頻次




書目名稱Information Processing in Medical Imaging被引頻次學(xué)科排名




書目名稱Information Processing in Medical Imaging年度引用




書目名稱Information Processing in Medical Imaging年度引用學(xué)科排名




書目名稱Information Processing in Medical Imaging讀者反饋




書目名稱Information Processing in Medical Imaging讀者反饋學(xué)科排名

Flinch

歡樂中國

0302-9743 sessions deal with segmentation, shape analysis, statistical methods, image reconstruction, microscopic image analysis, computer aided diagnosis, diffusion imaging, functional brain analysis, registration and other related topics.978-3-642-22091-3978-3-642-22092-0Series ISSN 0302-9743 Series E-ISSN 1611-3349

syncope

Segmentation of 3D RF Echocardiography Using a Multiframe Spatio-temporal Predictorthm. Results are generated using between 2 and 5 frames of RF data for each segmentation and are validated by comparison with manual tracings and automated B-mode boundary detection using standard (Chan and Vese-based) level sets on echocardiographic images from 27 3D sequences acquired from 6 canine studies.

宿醉

Optimal Graph Based Segmentation Using Flow Lines with Application to Airway Wall Segmentation and larger area of overlap than are obtained with recently published graph based methods..Airway abnormality measurements obtained with the method on 480 scan pairs from a lung cancer screening trial are reproducible and correlate significantly with lung function.

VICT

COMMA

Parameterization-Invariant Shape Statistics and Probabilistic Classification of Anatomical Surfacesuccess of this model through improved random sampling and a higher classification performance. We study brain structures and present classification results for Attention Deficit Hyperactivity Disorder. Using the mean and covariance structure of the data, we are able to attain an 88% classification rate.

hemoglobin

嘲弄

莊嚴(yán)