TY - GEN
T1 - Dilation and Erosion for Left Atrium Scar Segmentation
AU - Jiang, Jinyi
AU - Liu, Tianyi
AU - Jiang, Haochuan
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - Segmenting the left atrium (LA) scar from a magnetic resonance imaging (MRI) dataset is a challenging task because of the low quality of the source image and the uncertain location and the small shape of the LA scar. Recent studies always focus on optimizing the structure of the model while ignoring optimizing the preprocessing method when segmenting the LA scar. Since LA scars always appear around the boundary of LAs which is easier to predict, boundary information can be used as auxiliary information to help scar prediction. In order to alleviate the inaccurate prediction effect that the LA boundary brings, we use the expansion method to increase useful image foreground information. At the same time, since we only need to draw on the information of the LA boundary, the prediction inside LA is interfering with information for us. Therefore, we apply the corrosion method to remove the useless image foreground information. In summary, in this research, we investigate the effectiveness of two popular computer vision techniques, i.e., dilation and erosion, on the segmented LA, to help predict left atrium scar. Results on the LAScar dataset demonstrate they are useful as preprocessing approaches in related tasks.
AB - Segmenting the left atrium (LA) scar from a magnetic resonance imaging (MRI) dataset is a challenging task because of the low quality of the source image and the uncertain location and the small shape of the LA scar. Recent studies always focus on optimizing the structure of the model while ignoring optimizing the preprocessing method when segmenting the LA scar. Since LA scars always appear around the boundary of LAs which is easier to predict, boundary information can be used as auxiliary information to help scar prediction. In order to alleviate the inaccurate prediction effect that the LA boundary brings, we use the expansion method to increase useful image foreground information. At the same time, since we only need to draw on the information of the LA boundary, the prediction inside LA is interfering with information for us. Therefore, we apply the corrosion method to remove the useless image foreground information. In summary, in this research, we investigate the effectiveness of two popular computer vision techniques, i.e., dilation and erosion, on the segmented LA, to help predict left atrium scar. Results on the LAScar dataset demonstrate they are useful as preprocessing approaches in related tasks.
KW - Left atrium scar segmentation
KW - Preprocessing method
UR - http://www.scopus.com/inward/record.url?scp=85187783912&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-8498-5_39
DO - 10.1007/978-981-99-8498-5_39
M3 - Conference Proceeding
AN - SCOPUS:85187783912
SN - 9789819984978
T3 - Lecture Notes in Networks and Systems
SP - 467
EP - 473
BT - Advances in Intelligent Manufacturing and Robotics - Selected Articles from ICIMR 2023
A2 - Tan, Andrew
A2 - Zhu, Fan
A2 - Jiang, Haochuan
A2 - Mostafa, Kazi
A2 - Yap, Eng Hwa
A2 - Chen, Leo
A2 - Olule, Lillian J. A.
A2 - Myung, Hyun
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Intelligent Manufacturing and Robotics, ICIMR 2023
Y2 - 22 August 2023 through 23 August 2023
ER -