Computer vision (also known as "machine vision") is the construction of explicit meaningful descriptions of a physical objects or other observable phenomena from images. Computer vision, the focus of the group's research, has a very wide range of applications from medical diagnosis to seeing robots, from particle physics to geological surveying, and from missile defense to quality control.Wherever images play an important role in understanding a problem, there is a potential application for computer vision. A subset of topics in the field of computer vision include image segmentation and formation, edge detection, region growing and shape description.
Relationships to Other Fields:
Computer vision is closely related to a number of different fields, yet there are clear distinctions between them. The goal of computer vision is to extract information from an image. That information may be a geometric description of an object, the distance between the object and the source, whether an airplane is an enemy or ally, or whether a patient has cancer.
The related field of image processing transforms an image into another image. The output image may be compressed, enhanced, or have corrections for blurring from motion. Often these algorithms are useful in the early stages of computer vision it is helpful to preprocess images to get them ready for computer analysis.
Computer graphics generates images from a mathematical description. In a sense, this is the opposite of computer vision, which returns descriptions of a scene based on an image. Computer graphics is image synthesis, while computer vision is image analysis.
Other fields which are tightly knit with computer vision are pattern recognition, artificial intelligence, statistics, and psychophysics.
Medical Image Analysis:
The current primary research goal of the group is the development of a medical computer assisted diagnosis (CAD) system. The focus of this research, in collaboration with the Weill Medical Cornell at Cornell, is to evaluate patient health and diagnose disease (especially cancer) through analysis of three-dimensional images from CT scans. Current programs are directed towards detecting pulmonary nodules in whole lung scans and the diagnosis of nodules from high resolution CT scans. We have installed a direct connection to the New York Hospital PACS system and directly access the Hospital image database. Projects are available on the following image analysis issues: Advanced 3D image segmentation, 3D visualization and animation, medical database developed, computer medical diagnosis methods including neural networks.
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