1.Multi-phase CT synthesis-assisted segmentation of abdominal organs
Pinyu HUANG ; Liming ZHONG ; Kaiyi ZHENG ; Zeli CHEN ; Ruolin XIAO ; Xianyue QUAN ; Wei YANG
Journal of Southern Medical University 2024;44(1):83-92
Objective To propose a method for abdominal multi-organ segmentation assisted by multi-phase CT synthesis.Methods Multi-phase CT synthesis for synthesizing high-quality CT images was used to increase the information details for image segmentation.A transformer block was introduced to help to capture long-range semantic information in cooperation with perceptual loss to minimize the differences between the real image and synthesized image.Results The model was trained using multi-phase CT dataset of 526 total cases from Nanfang Hospital.The mean maximum absolute error(MAE)of the synthesized non-contrast CT,venous phase contrast-enhanced CT(CECT),and delay phase CECT images from arterial phase CECT was 19.192±3.381,20.140±2.676 and 22.538±2.874,respectively,which were better than those of images synthesized using other methods.Validation of the multi-phase CT synthesis-assisted abdominal multi-organ segmentation method showed an average dice coefficient of 0.847 for the internal validation set and 0.823 for the external validation set.Conclusion The propose method is capable of synthesizing high-quality multi-phase CT images to effectively reduce the errors in registration between different phase CT images and improve the performance for segmentation of 13 abdominal organs.
2.Multi-phase CT synthesis-assisted segmentation of abdominal organs
Pinyu HUANG ; Liming ZHONG ; Kaiyi ZHENG ; Zeli CHEN ; Ruolin XIAO ; Xianyue QUAN ; Wei YANG
Journal of Southern Medical University 2024;44(1):83-92
Objective To propose a method for abdominal multi-organ segmentation assisted by multi-phase CT synthesis.Methods Multi-phase CT synthesis for synthesizing high-quality CT images was used to increase the information details for image segmentation.A transformer block was introduced to help to capture long-range semantic information in cooperation with perceptual loss to minimize the differences between the real image and synthesized image.Results The model was trained using multi-phase CT dataset of 526 total cases from Nanfang Hospital.The mean maximum absolute error(MAE)of the synthesized non-contrast CT,venous phase contrast-enhanced CT(CECT),and delay phase CECT images from arterial phase CECT was 19.192±3.381,20.140±2.676 and 22.538±2.874,respectively,which were better than those of images synthesized using other methods.Validation of the multi-phase CT synthesis-assisted abdominal multi-organ segmentation method showed an average dice coefficient of 0.847 for the internal validation set and 0.823 for the external validation set.Conclusion The propose method is capable of synthesizing high-quality multi-phase CT images to effectively reduce the errors in registration between different phase CT images and improve the performance for segmentation of 13 abdominal organs.