III: Small: Collaborative Research: Modeling, Detection, and Analysis of Branching Structures in Medical Imaging

University Of Pennsylvania, Philadelphia PA

Investigators

Abstract

Detection and analysis of branching structures and/or texture is very challenging; it arises in many areas of science and engineering (e.g., medical images, chemical compounds, etc). The objective of this proposal is to develop novel approaches to model, detect, and analyze branching structures obtained from multimodality data. Such representation and analysis tools are expected to make many complex problems more tractable. Examples include identifying and recognizing a large number of structure classes; discovering new relationships among structure, texture, and function or pathology; evaluating hypotheses; developing modeling tools; assisting with surgical design; and managing medical image data efficiently. Specifically, the investigators plan to explore three research topics under this project: (1) To develop descriptors of branching structures and texture, and knowledge discovery tools that will enable hypotheses generation and evaluation and improve modeling of branching structures; (2) To design automated algorithms and a flexible framework to detect branching structures. The investigators are especially interested in addressing challenges of occlusion and topology change; (3) To demonstrate the applicability of the proposed tools to breast imaging by building a prototype database of images from various modalities and associated clinical data that will provide advanced analysis and visualization capabilities. Though the investigators use breast imaging as the driving application, the proposed project is expected to provide software and data resources that can assist clinical tasks and scientific discoveries in general. Developing automated tools to effectively characterize, detect, and classify tree-like structures in images would provide great insight into the relationship between the branching topology and function or pathology. The investigators plan to further contribute to the medical/scientific community by disseminating the related software and annotated data sets. The educational goals include incorporating research findings to graduate courses at Temple (data mining course and medical image analysis seminar) and at the University of Pennsylvania (medical image analysis course).