LPM-GAN: Lumbar Paraspinal Muscle Segmentation Using a Generative Adversarial Network
文献类型：会议论文
| 作者 | Li HX(李海星)1,2,3,4; Luo HB(罗海波)1,2,3 ; Wang H(王欢)5; Yan CN(阎崇楠)5; Wang LB(王蓝博)5; Mu YM(穆月明)5; Liu YP(刘云鹏)1,2,3
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| 出版日期 | 2021 |
| 会议日期 | December 7-9, 2021 |
| 会议地点 | Kunming, China |
| 关键词 | Posterior lumbar surgeries paraspinal muscles MRI image automated segmentation generative adversarial network |
| 页码 | 1-7 |
| 英文摘要 | After posterior lumbar surgeries (PLS), the change of the cross-sectional area(CSA) and fatty infiltration (FI) of paraspinal muscle can deeply affect the muscle activity pattern and spinal stability. The objective of this work is to perform automated paraspinal muscle (multifidus and erector spine) segmentation in magnetic resonance imaging (MRI) image. However, no work has achieved the semantic segmentation of multifidus (MF) and erector spinae (ES) due to three unusual challenges: (1) the distribution of paraspinal muscle overlaps with the distribution of other anatomical structures; (2) the fascia between MF and ES is unclear; (3) the intra- and inter-patient shape is variable. In this paper, we proposed a generative adversarial network called LPM-GAN which contains a generator and a discriminator to resolve above challenges. The generator solves the high variability and variety of paraspinal muscle through extracting high-level semantics of images and preserving the paraspinal muscle anatomy. And then, the discriminator is trained to optimize the predicted mask to make it closer to ground truth. Finally, we obtain the CSA and FI of paraspinal muscle by utilizing Otsu. Extensive experiments on MRIs of 69 patients have demonstrated that LPM-GAN achieves high Recall of 0.931 and 0.904, and Dice coefficient of 0.920 and 0.903, which reveals the method is effective. |
| 源文献作者 | Chinese Society for Optical Engineering ; Science and Technology on Low-light-level Night Vision Laboratory |
| 产权排序 | 1 |
| 会议录 | 8th Symposium on Novel Photoelectronic Detection Technology and Applications
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| 会议录出版者 | SPIE |
| 会议录出版地 | Bellingham, USA |
| 语种 | 英语 |
| ISSN号 | 0277-786X |
| ISBN号 | 978-1-5106-5311-5 |
| 源URL | [http://ir.sia.cn/handle/173321/30792]  |
| 专题 | 沈阳自动化研究所_光电信息技术研究室 |
| 通讯作者 | Luo HB(罗海波) |
| 作者单位 | 1.Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Sciences, Shenyang 110016, China 2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China 4.University of Chinese Academy of Sciences, Beijing 100049, China 5.Department of Spine Surgery, Shengjing Hospital of China Medical University, Shenyang, China |
| 推荐引用方式 GB/T 7714 | Li HX,Luo HB,Wang H,et al. LPM-GAN: Lumbar Paraspinal Muscle Segmentation Using a Generative Adversarial Network[C]. 见:. Kunming, China. December 7-9, 2021. |
入库方式： OAI收割
来源：沈阳自动化研究所
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