Hepatocellular Carcinoma Segmentation from Digital Subtraction Angiography Videos Using Learnable Temporal Difference

نویسندگان

چکیده

Automatic segmentation of hepatocellular carcinoma (HCC) in Digital Subtraction Angiography (DSA) videos can assist radiologists efficient diagnosis HCC and accurate evaluation tumors clinical practice. Few studies have investigated from DSA videos. It shows great challenging due to motion artifacts filming, ambiguous boundaries tumor regions high similarity imaging other anatomical tissues. In this paper, we raise the problem videos, build our own dataset. We also propose a novel network called DSA-LTDNet, including sub-network, temporal difference learning (TDL) module liver region (LRS) sub-network for providing additional guidance. DSA-LTDNet is preferable latent information proactively boosting performance. All experiments are conducted on self-collected Experimental results show that increases DICE score by nearly 4% compared U-Net baseline.

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ژورنال

عنوان ژورنال: Lecture Notes in Computer Science

سال: 2021

ISSN: ['1611-3349', '0302-9743']

DOI: https://doi.org/10.1007/978-3-030-87240-3_2