Fu, Jie <br/><br/>
Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging.  [electronic resource] 

 -  Medical physics  Sep 2019 
 - 3788-3798 p.  digital 
<br/><br/> Publication Type: Journal Article 
<br/><br/><label>ISSN: </label>2473-4209 
<br/><br/><label>Standard No.: </label>10.1002/mp.13672  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Aged<br/>Aged, 80 and over<br/>Deep Learning<br/>Humans<br/>Image Processing, Computer-Assisted--methods<br/>Magnetic Resonance Imaging<br/>Male<br/>Middle Aged<br/>Pelvis--diagnostic imaging<br/>Prostatic Neoplasms--diagnostic imaging<br/>Retrospective Studies<br/>Tomography, X-Ray Computed