Treating patients with safe and effective radiation therapy depends critically on the precise identification of tumor and nearby normal tissues. This process, known as contouring, refers to identifying and outlining cancer and normal tissues in medical images.
Poor radiation planning has detrimental consequences on patient well-being. Radiation plans that deviate from protocol specifications have substantially decreased survival compared to patients with compliant radiation plans. Given the impact of contouring on patient outcomes, many contouring resources exist. However, practice guidelines rarely translate into real-world clinical practices, primarily due to ineffective methods of development, delivery, and access.
In collaboration with the department of Radiation Medicine at UCSD, we strive to identify and address shortcomings in radiation oncology education: our efforts aim to transform the traditional 1-on-1 healthcare training into personalized and timely AI and peer support. We also plan to introduce novel sketching techniques in Virtual Reality to support 3D exploration and annotation in medical images.
Funding and External Collaborations
iContour is funded by Agency for Healthcare Research and Quality (AHRQ). It is a collaboration between the HXI Lab and a number of radiation oncology faculty and residents at UCSD school of medicine.