Machine Learning Meets Medical Imaging
First International Workshop, MLMMI 2015, Held in Conjunction with ICML 2015, Lille, France, July 11, 2015, Revised Selected Papers
Buch in deiner Nähe kaufen
Beschreibung
Normal
0
false
false
false
EN-US
X-NONE
X-NONE
/* Style Definitions */
table.MsoNormalTable
{mso-style-name:"Table Normal";
mso-tstyle-rowband-size:0;
mso-tstyle-colband-size:0;
mso-style-noshow:yes;
mso-style-priority:99;
mso-style-qformat:yes;
mso-style-parent:"";
mso-padding-alt:0in 5.4pt 0in 5.4pt;
mso-para-margin:0in;
mso-para-margin-bottom:.0001pt;
mso-pagination:widow-orphan;
font-size:11.0pt;
font-family:"Calibri","sans-serif";
mso-ascii-font-family:Calibri;
mso-ascii-theme-font:minor-latin;
mso-fareast-font-family:"Times New Roman";
mso-fareast-theme-font:minor-fareast;
mso-hansi-font-family:Calibri;
mso-hansi-theme-font:minor-latin;
mso-bidi-font-family:"Times New Roman";
mso-bidi-theme-font:minor-bidi;}
This book constitutes the revised selected papers of the
First International Workshop on Machine Learning in Medical Imaging, MLMMI
2015, held in July 2015 in Lille, France, in conjunction with the 32nd
International Conference on Machine Learning, ICML 2015.
The 10 papers presented in this volume were carefully
reviewed and selected for inclusion in the book. The papers communicate the
specific needs and nuances of medical imaging to the machine learning community
while exposing the medical imaging community to current trends in machine
learning.
Includes supplementary material: sn.pub/extras
Autor*in
Kanwal Bhatia
Themen in »Machine Learning Meets Medical Imaging«
bioinformatics computational biology computer vision machine learning mathematical analysis Alzheimer's disease brain classification clinical classification computer-aided detection system gaussian processes graph kernel interpretability learning MRI