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An adaptive algorithm that formulates an energy based stochastic segmentation with a level set methodology is proposed.The hybrid method uses global and local energies, which are efficient in matching, segmenting and tracing anatomic structures by exploiting constraints computed from the data of the image. The algorithm performs autonomous stochastic segmentation of tumor in Magnetic Resonance Imaging...
Brain tumor has remained one of the key causes of death in people of all ages. One way to increase survival rate amongst patients is to correctly diagnose cancer in its early stages. There are several classifiers which can classify cancer images with high accuracy. The goal of this paper was to present a brief survey of the main machine learning methods used in literature to classify brain tumor in...
Gene annotation is by nature a computationally intensive problem, as it needs to process huge data size of DNA sequences. This forces the need to look for alternate ways of implementing algorithms to predict exons. The paper presents an accelerator for indexing DNA sequences. The accelerator effectively exploits the 3-periodicity property exhibited by protein coding regions and indicates their presence...
Gene annotation is by nature a computationally intensive problem, as it needs to process huge data size of DNA sequences. This forces the need to look for alternate ways of implementing algorithms to predict exons. The paper presents an accelerator for indexing DNA sequences. The accelerator effectively exploits the 3-periodicity property exhibited by protein coding regions and indicates their presence...
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