Gary Gelfand

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Modern multislice computed tomography (CT) scanners produce isotropic CT images with a thickness of 0.6 mm. These CT images offer detailed information of lung cavities, which could be used for better surgical planning of treating lung cancer. The major challenge for developing a surgical planning system is the automatic segmentation of lung lobes by(More)
PURPOSE The major hurdle for three-dimensional display of lung lobes is the automatic recognition of lobar fissures, boundaries of lung lobes. Lobar fissures are difficult to recognize due to their variable shape and appearance, along with the low contrast and high noise inherent in computed tomographic (CT) images. An algorithm for recognizing the major(More)
Advanced multi-slice CT scanners produce isotropic CT images, which have pixel dimensions equal to their image thicknesses of 0.6 mm. Comparing to clinical standard CT images with a thickness of 2.5 - 7.0 mm, isotropic CT images have clearly visible lobar fissures. This poses a challenge for developing automatic algorithms to identify the fissure locations(More)
Identification of lobar fissures in human lungs is a non-trivial task due to their variable shape and appearance, along with the low contrast and high noise in computed tomographic (CT) images. Pathologies in the lungs can further complicate this identification by deforming and/or disrupting the lobar fissures. Current algorithms rely on the general anatomy(More)
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