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SPIE Professional October 2016

Science of deep learning and precision medicine at center stage for SPIE Medical Imaging 2017

An emphasis on precision medicine returns to SPIE Medical Imaging in 2017. The annual event for scientists and radiologists in image processing, imaging informatics, digital pathology, computed tomography, and other technologies for medical imaging will be held 11-16 February in Orlando, FL (USA).

logo for SPIE Medical ImagingMedical imaging has an important role to play in the emerging approach to individually targeted disease treatment and prevention. Conferences on image-guided procedures, computer-aided diagnoses, quantitative imaging, and other topics related to the science of medical imaging will provide attendees with a forum to discuss the latest advancements in the field.

A special session at SPIE Medical Imaging 2017 will be dedicated to the “PROSTATEx Challenge” on quantitative image analysis methods for the diagnostic classification of clinically significant prostate lesions. Participants will have a unique opportunity to compare their algorithms with those of others from academia, industry, and government in a structured, direct way using the same data sets.

The challenge is sponsored by SPIE, with support of the American Association of Physicists in Medicine (AAPM) and the National Cancer Institute (NCI).

The database for the challenge will be released in November and December 2016 and will contain approximately 350 MRI cases, each from a distinct patient at a single exam time.

The two top-performing participants will present their methods during this session and receive free conference registration. Challenge participants who submit test set classification results by 6 January 2017 will be invited to present a poster and demonstrate their algorithm at the live demonstration computer-aided diagnosis (CAD) workshop during the symposium.

Participants in the PROSTATEx Challenge are encouraged to submit their work to the SPIE CAD conference proceedings volume as well as for peer review to the Journal of Medical Imaging.

photo of Greg Corrado An all-symposium plenary session will put a particular focus on applying “deep learning” to medical imaging. Greg Corrado, a senior researcher in artificial intelligence, computational neuroscience, and machine learning at Google (USA), will discuss how computer software can be programmed to interpret and evaluate the scientific data found deep within medical images.

Corrado has a PhD in neuroscience and has served as one of the founding members and the co-technical lead of Google’s large-scale deep neural networks project. Begun in 2011 as a “fun” project at Google, the Google Brain Project now employs a team of more than 40 scientists and engineers.

Other topics at nine conferences at SPIE Medical Imaging include tomographic image reconstruction, computational models, image-guided therapies, visual perception, and image data management.

Symposium chairs for 2017 are Berkman Sahiner of the US Food and Drug Administration and SPIE member Leonard Berliner of Weill Cornell Medical College and New York Methodist Hospital (USA).

Read more about SPIE Medical Imaging 2017.


DOI: 10.1117/2.4201610.11

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