530-02-008 ISMRM Abstract

One Touch Patient Registration and Smart MR Scan Planning Using Deep Learning

Primary: Analysis Methods - Segmentation and Detection

Secondary: Analysis Methods - Classification and Prediction

530-02-008 · Registration, Atlases, and Motion · Wednesday, 13 May, 8:20 AM–10:10 AM · Meeting Room 2.60

Keywords: Machine Learning/Artificial Intelligence MRI Workflow optimzation Work efficiency Sensor Deep Learning Segmentation

Accepted

SAGNIK GHOSH ¹, SANKET MALI¹, HARIKRISHNA RAI¹

¹Artificial intelligence for Magnetic Resonance Imaging, GE HealthCare (Bengaluru, India), Bengaluru, India

Presenting Author: SAGNIK GHOSH

Synopsis

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References

1. Body surface area prediction in normal-weight and obese patients. doi:https://doi.org/10.1152/ajpendo.2001.281.3.E586 [doi]

2. Estimation of Total Body Weight in Obese Patients. doi:https://doi.org/10.1016/j.amj.2009.02.002 [doi]

3. Z. Jin, J. Huang, W. Wang, A. Xiong and X. Tan, "Estimating Human Weight From a Single Image," in IEEE Transactions on Multimedia, vol. 25, pp. 2515-2527, 2023. doi:https://doi.org/10.1109/TMM.2022.3147945 [doi]

4. Ichikawa, S., Hamada, M. & Sugimori, H. A deep-learning method using computed tomography scout images for estimating patient body weight. Sci Rep 11, 15627 (2021).doi:https://doi.org/10.1038/s41598-021-95170-9 [doi]

5. https://github.com/lyuwenyu/RT-DETR

6. https://github.com/HRNet/HRNet-Human-Pose-Estimation

7. https://docs.pytorch.org/vision/main/models/generated/torchvision.models.video.r3d_18.html

8. https://huggingface.co/docs/timm/v0.9.2/en/models/inception-resnet-v2

9. Singh, V., Chang, Yj., Ma, K., Wels, M., Soza, G., Chen, T. (2014). Estimating a Patient Surface Model for Optimizing the Medical Scanning Workflow. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds) Medical Image Computing and Computer-Assisted Intervention. doi: https://doi.org/10.1007/978-3-319-10404-1_59 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/530-02-008