Focus on detailed imagery by giving importance to inter-slice connectivity by a divide and conquer approach. In context of medical imaging decreasing processing time will help significantly as this algorithm claims to do - smplifying diagnosis by colating series of 2D images derived from various methods into a 3D model. Level of detail is improvement over existing algorithms. Basic concept of the marching cubes algorithm mentioned as the 7 steps is quite easy to understand though the calculations seem very intricate.
This was the first time I read about how actual algorithms and 3D modeling is done for medical imagery. It was very interesting to read and I was surprised that it was implemented in simple C. It is also great that this algorithm considers a variety of medical data, from CT scans, MRI scans and SPECT scans. Having seen MRI scan reports and CT scans, and then the results of the 3D modeling of the same with this algorithm, I can clearly see the value, depth, visibility and understanding that this algorithm adds to it.
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