A modified UNet-based semantic segmentation architecture for pancreas tumour detection
by Banavathu Sridevi; B. John Jaidhan
International Journal of Bioinformatics Research and Applications (IJBRA), Vol. 20, No. 1, 2024

Abstract: For computer aided diagnosis, computerised organ segmentation is a crucial but complicated task. The anatomy of the pancreas varies greatly and it is an abdominal organ. Especially when compared to other organs like the liver, heart, or kidneys, this prevents earlier segmentation approaches from obtaining high accuracy levels. To address this issue, we proposed a modification in UNet architecture called DAH-UNet that combines residual blocks, a rebuilt atrous spatial pyramid pooling (ASPP), and depth-wise convolutions. Also, a hybrid loss function which is explicitly aware of the boundaries is another thing we suggest. Experiments were conducted on two publicly available dataset and proved better in some metrics as compare to existing semantic segmentation models.

Online publication date: Thu, 14-Mar-2024

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