Surgical Planning Laboratory - Brigham & Women's Hospital - Boston, Massachusetts USA - a teaching affiliate of Harvard Medical School

Surgical Planning Laboratory

William M. Wells III, Ph.D. (aka Sandy Wells)

William M. Wells III (aka Sandy Wells)
Professor of Radiology
Department of Radiology
Harvard Medical School and
Brigham and Women's Hospital

Member of the Affiliated Faculty of the Harvard-MIT Division of Health Sciences and Technology

Research Scientist, MIT CSAIL

I am a researcher in medical image analysis with the Surgical Planning Laboratory, a unit of the MRI division of the Radiology Department of Brigham and Women's Hospital, Harvard Medical School. I maintain an active collaboration with the MIT Computer Science and Artificial Intelligence Laboratory, where I have worked with a talented group of graduate students. I am also affiliated with the Harvard-MIT Division of Health Sciences and Technology.

Modern medical images contain vast amounts of anatomical information. Much of this information is accessible to diagnostic radiologists, in part because people (in contrast to computers) are very good at image interpretation. The anatomical information latent in such images is also valuable for disease and neuroscience research, as well as for drug trials. The quantitative analysis of medical images by computer, however, remains challenging. Among the most basic capabilities of medical image analysis are segmentation, the process of assigning labels to structures in images, and registration, the process of placing different images into anatomical agreement.

My work has focused primarily on the analysis of structural and functional MRI, including segmentation and registration of MRI, with some emphasis on applications in image-guided surgery. The figure on the upper right illustrates the white matter surface of a brain that was segmented from MRI using Adaptive Segmentation of MRI (the "EM Segmenter") .

My research in medical image registration concerns the use of Mutual Information as a criterion for image fusion. This approach has become the de-facto standard for multi-modality problems. Implementations of this method are available in 3D Slicer, our open-source platform for medical image analysis, and in ITK, an NIH sponsored segmentation and registration library.

In addition to morphological analysis, I am also interested in univariate and multivariate analysis of functional MRI.

If you want to do research training with Dr. Wells, please fill out this form.

In June 2013 I organized the 2013 meeting of Information Processing In Medical Imaging (IPMI 2013), held near Monterey California.

Publications

Contact info:

E-mail: sw at bwh.harvard.edu

William Wells
Surgical Planning Laboratory
Department of Radiology
Brigham and Women's Hospital
75 Francis St.
Boston, MA 02115

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