Automatic Colorectal Segmentation with Convolutional Neural Network. Guachi, L., Guachi, R., Bini, F., & Marinozzi, F. Computer-Aided Design and Applications, 16(5):836-845, 2019. ![Automatic Colorectal Segmentation with Convolutional Neural Network [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website doi abstract bibtex 1 download This paper presents a new method for colon tissues segmentation on Computed Tomography images which takes advantages of using deep and hierarchical learning about colon features through Convolutional Neural Networks (CNN). The proposed method works robustly reducing misclassified colon tissues pixels that are introduced by the presence of noise, artifacts, unclear edges, and other organs or different areas characterized by the same intensity value as the colon. Patch analysis is exploited for allowing the classification of each center pixel as colon tissue or background pixel. Experimental results demonstrate the proposed method achieves a higher effectiveness in terms of sensitivity and specificity with respect to three state-of the art methods.
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title = {Automatic Colorectal Segmentation with Convolutional Neural Network},
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abstract = {This paper presents a new method for colon tissues segmentation on Computed Tomography images which takes advantages of using deep and hierarchical learning about colon features through Convolutional Neural Networks (CNN). The proposed method works robustly reducing misclassified colon tissues pixels that are introduced by the presence of noise, artifacts, unclear edges, and other organs or different areas characterized by the same intensity value as the colon. Patch analysis is exploited for allowing the classification of each center pixel as colon tissue or background pixel. Experimental results demonstrate the proposed method achieves a higher effectiveness in terms of sensitivity and specificity with respect to three state-of the art methods.},
bibtype = {article},
author = {Guachi, Lorena and Guachi, Robinson and Bini, Fabiano and Marinozzi, Franco},
doi = {10.14733/cadaps.2019.836-845},
journal = {Computer-Aided Design and Applications},
number = {5}
}
Downloads: 1
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