We develop new algorithms for medical image analysis and visualization of medical imagery.
We build computational models of anatomical and functional variability from medical images and develop methods for making predictions for new subjects based on images and prior information. We collaborate extensively with practicing clinicians, clinical researchers and neuroscientists to apply these methods in surgical planning and navigation, population studies and basic neuroscience.
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We develop novel algorithms for neuroimage segmentation, registration, generative modeling, and joint modeling of brain structure with clinical and genetic data.
By mapping the volumes of objects, rather than their surfaces, a new technique could yield solutions to computer graphics problems in animation and CAD.
Scientists employ an underused resource — radiology reports that accompany medical images — to improve the interpretive abilities of machine learning algorithms.
People who suffer a stroke often undergo a brain scan at the hospital, allowing doctors to determine the location and extent of the damage. Researchers who study the effects of strokes would love to be able to analyze these images, but the resolution is often too low for many analyses.
Researchers from MIT, Boston Children's Hospital, and Massachusetts General Hospital have joined forces in an ambitious new project to use magnetic resonance imaging (MRI) to evaluate the health of fetuses.
Typically, fetal development is monitored with ultrasound imaging, which is cheap and portable and can gauge blood flow through the placenta, the organ in the uterus that delivers nutrients to the fetus. But MRI could potentially measure the concentration of different chemicals in the placenta and in fetal organs, which may have more diagnostic value.
Researchers at CSAIL and Boston Children’s Hospital have developed a system that can take MRI scans of a patient’s heart and, in a matter of hours, convert them into a tangible, physical model that surgeons can use to plan surgery.The models could provide a more intuitive way for surgeons to assess and prepare for the anatomical idiosyncrasies of individual patients. “Our collaborators are convinced that this will make a difference,” says professor and CSAIL principal investigator Polina Golland, who led the project. “The phrase I heard is that ‘surgeons see with their hands,’ that the perception is in the touch.” This fall, seven cardiac surgeons at Boston Children’s Hospital will participate in a study intended to evaluate the models’ usefulness.
