Change Detection and Analysis of Metastatic Brain Cancer in T1 MRI

2017 Research Internship Project

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Faculty Name

April Khademi

Project Title

Change Detection and Analysis of Metastatic Brain Cancer in T1 MRI

Project Description

Metastatic brain tumors (MBTs) occur in 8-10% of patients diagnosed with primary cancers outside the brain and 24-45% of patients with metastatic cancer. Brain metastasis is associated with a two-year overall survival of 8%. Accurate detection and follow-up assessment of MBTs are critical factors for better prognosis, selecting the most appropriate treatment (e.g., chemotherapy, radiation, or surgery), and most importantly radiation planning. Critical to treatment planning and follow-up is accurate volume assessment, due to the increased risk of both local progression and distant new brain metastases. During follow-up, serial volumetric imaging is obtained every 2–3 months, resulting in a large amount of data to process and demanding workload for radiologists. Moreover, user subjectivity results in the potential for increased error rates in both detection and volume assessment, especially in the detection of small MBTs and subtle volume changes. The development of an automated computer-aided diagnostic tool that quantitatively tracks changes in MBT volume over time and detects new or resolving MBTs would have great clinical value as it can increase radiologists’ efficiency and accuracy. This is the focus of the project.

Student Responsibility

The specific duties and responsibilities of the RA includes: 1) literature review on related image processing methods, 2) organization of the data, 3) downloading/using existing software tools to preprocess the data, 4) algorithm development, 5) communication of results to project team.

Specific Requirements

Good outcomes in Signals and Systems and related courses