In this work, experimental setups and software algorithms were written, and implemented on medical imaging modalities to illustrate the importance of using the computer generated holography to create holograms and spatial light modulators to reconstruct them.
We develop a computerized system for evaluation of alloimplant procedures in dentistry from x-ray images. The goal of this system is to help clinicians make more accurate evaluation of their surgical procedures as well as to guide them in selecting the most appropriate alloimplant material in an objective manner. A study was conducted whereby three types of alloimplant materials were inserted in surgical defects in the tibia of dogs. Each animal had four such defects for the three different materials in addition to a control defect that was intentionally left empty. The defect locations were imaged using x-rays at periodic intervals starting immediately after the operation. The animals were sacrificed at different times after the surgical operation. The acquired images were paired with their correct diagnosis and split into two sets representing the learning and testing data for our computerized system. The plain x-ray films were scanned using a standard film digitizer and standardized in size and intensity using a step wedge that was imaged beside the region of interest. A set of first and second order textural and radiometric parameters were extracted from each alloimplant location outlined by the radiographer to describe its clinical status in a quantitative manner.
We propose a computerized system to accurately point laser to the diseased areas within the retina based on predetermined treatment planning. The proposed system consists of a fundus camera using red-free illumination mode interfaced to a computer that allows real-time capturing of video input. The first image acquired is used as the reference image for treatment planning. A new segmentation technique was developed to accurately discern the image features using deformable models. A grid of seed contours over the whole image is initiated and allowed to deform by splitting and/or merging according to preset criteria until the whole vessel tree is extracted. This procedure extracts the whole area of small vessels but only the boundaries of the large vessels. Correlating the image with a one-dimensional Gaussian filter in two perpendicular directions is used to extract the core areas of such vessels. Faster segmentation can be obtained for subsequent images by automatic registration to compensate for eye movement and saccades. Comparing the two sets of landmark points using a least-squares error provide an optimal transformation between the two point sets. This allows for real-time location determination and tracking of treatment positions.
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