Interdisciplinary research spanning computer science, mathematics, and Data Science applied to science and engineering domains. Most recently this has been focused on data visualization for big and high dimensional data, using tools from statistical/machine learning and using web technology for exploration. Recent domains have included remote sensing, climate science, medical imaging and computer vision. For more information see http://www-cs.ccny.cuny.edu/~grossberg Supervisors: Raul Bott
Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2001
... computed, stored, and matched efficiently. In figure 1 we show an example of a mul-tiresoluti... more ... computed, stored, and matched efficiently. In figure 1 we show an example of a mul-tiresolution histogram. The first row shows the image pyra-mid and the second row the multiresolution histogram. In ad-dition to the initial ...
Proceedings of the 10th IEEE International Conference on Information Technology and Applications in Biomedicine, 2010
... Yu-Chi Hu, Michael D. Grossberg and Gig S. Mageras ... boundary terms (edge costs in graph) i... more ... Yu-Chi Hu, Michael D. Grossberg and Gig S. Mageras ... boundary terms (edge costs in graph) in our energy function for graph cut minimization is reduced to 40% to 50% of original number of nodes in ROL We measure the CPU time in one liver case on a dual-Xeon workstation. ...
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2008
Planning radiotherapy and surgical procedures usually require onerous manual segmentation of anat... more Planning radiotherapy and surgical procedures usually require onerous manual segmentation of anatomical structures from medical images. In this paper we present a semi-automatic and accurate segmentation method to dramatically reduce the time and effort required of expert users. This is accomplished by giving a user an intuitive graphical interface to indicate samples of target and non-target tissue by loosely drawing a few brush strokes on the image. We use these brush strokes to provide the statistical input for a Conditional Random Field (CRF) based segmentation. Since we extract purely statistical information from the user input, we eliminate the need of assumptions on boundary contrast previously used by many other methods, A new feature of our method is that the statistics on one image can be reused on related images without registration. To demonstrate this, we show that boundary statistics provided on a few 2D slices of volumetric medical data, can be propagated through the ...
We present fast methods for separating the direct and global illumination components of a scene m... more We present fast methods for separating the direct and global illumination components of a scene measured by a camera and illuminated by a light source. In theory, the separation can be done with just two images taken with a high frequency binary illumination pattern and its complement. In practice, a larger number of images are used to overcome the optical and resolution limitations of the camera and the source. The approach does not require the material properties of objects and media in the scene to be known. However, we require ...
Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2001
... computed, stored, and matched efficiently. In figure 1 we show an example of a mul-tiresoluti... more ... computed, stored, and matched efficiently. In figure 1 we show an example of a mul-tiresolution histogram. The first row shows the image pyra-mid and the second row the multiresolution histogram. In ad-dition to the initial ...
Proceedings of the 10th IEEE International Conference on Information Technology and Applications in Biomedicine, 2010
... Yu-Chi Hu, Michael D. Grossberg and Gig S. Mageras ... boundary terms (edge costs in graph) i... more ... Yu-Chi Hu, Michael D. Grossberg and Gig S. Mageras ... boundary terms (edge costs in graph) in our energy function for graph cut minimization is reduced to 40% to 50% of original number of nodes in ROL We measure the CPU time in one liver case on a dual-Xeon workstation. ...
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2008
Planning radiotherapy and surgical procedures usually require onerous manual segmentation of anat... more Planning radiotherapy and surgical procedures usually require onerous manual segmentation of anatomical structures from medical images. In this paper we present a semi-automatic and accurate segmentation method to dramatically reduce the time and effort required of expert users. This is accomplished by giving a user an intuitive graphical interface to indicate samples of target and non-target tissue by loosely drawing a few brush strokes on the image. We use these brush strokes to provide the statistical input for a Conditional Random Field (CRF) based segmentation. Since we extract purely statistical information from the user input, we eliminate the need of assumptions on boundary contrast previously used by many other methods, A new feature of our method is that the statistics on one image can be reused on related images without registration. To demonstrate this, we show that boundary statistics provided on a few 2D slices of volumetric medical data, can be propagated through the ...
We present fast methods for separating the direct and global illumination components of a scene m... more We present fast methods for separating the direct and global illumination components of a scene measured by a camera and illuminated by a light source. In theory, the separation can be done with just two images taken with a high frequency binary illumination pattern and its complement. In practice, a larger number of images are used to overcome the optical and resolution limitations of the camera and the source. The approach does not require the material properties of objects and media in the scene to be known. However, we require ...
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Papers by Michael D Grossberg