Abstract
Computed tomography (CT) is the preferred imaging modality for diagnosis of hemorrhage. The hematoma appears as hyper intense mass in the image. Computer aided diagnosis assists clinicians for making a better prediction and helps in surgery planning. Computer assistive method based on random walker is proposed for detection and delineation of hemorrhagic mass or hematoma from Computed Tomography (CT) volumes. 20 patients affected by hemorrhage is considered for this study. Each subject’s image has a size of 512 × 512 × 96. Every case has 96 images. In a CT volume each case has 96 slices. Each slice is of 512 × 512. The slice, which contains hematoma mass or ischemic lesion, is selected using one layer autoencoder. 60% of the patient volume is used for training and 40% of the patient volume is used for testing. The training accuracy of auto encoder was 100%, and testing accuracy was 99.5%. After the slices are classified as healthy and non-healthy, k-means clustering was applied on non-healthy slices for localization of hematoma. Random walker algorithm was applied on the localized lesion for delineation of hematoma from CT images. The computer generated output is compared with the manually delineated output with the help of similarity indices. The Dice similarity index and Jaccard coefficient was calculated as 0.768 ± 0.101 and 0.634 ± 0.128 respectively. The proposed algorithm suggests an alternate method for detection of hematoma using CT images.
M. K. Nag and A. Vupputuri—Equally contributed
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Acknowledgements
MK Nag would like to acknowledge Council of Scientific and Industrial Research, New Delhi, Senior research fellowship grant (No: 9/81(1296)/17) for financial assistance. All the authors would like to acknowledge EKO diagnostics for clinical inputs and providing the data for accomplishing this study.
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Nag, M.K., Vupputuri, A., Chatterjee, S., Sadhu, A.K., Chatterjee, J., Ghosh, N. (2019). Delineation of Hemorrhagic Mass from CT Volume. In: Lightner, N. (eds) Advances in Human Factors and Ergonomics in Healthcare and Medical Devices. AHFE 2018. Advances in Intelligent Systems and Computing, vol 779. Springer, Cham. https://doi.org/10.1007/978-3-319-94373-2_14
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DOI: https://doi.org/10.1007/978-3-319-94373-2_14
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