H-SegMed: a hybrid method for prostate segmentation in TRUS images via improved closed principal curve and improved enhanced machine learning

T Peng, C Tang, Y Wu, J Cai - International Journal of Computer Vision, 2022 - Springer
Prostate segmentation is an important step in prostate volume estimation, multi-modal image
registration, and patient-specific anatomical modeling for surgical planning and image …

H-SegMed: A Hybrid Method for Prostate Segmentation in TRUS Images via Improved Closed Principal Curve and Improved Enhanced Machine Learning

T Peng, C Tang, Y Wu, J Cai - International Journal of …, 2022 - research.polyu.edu.hk
Prostate segmentation is an important step in prostate volume estimation, multi-modal image
registration, and patient-specific anatomical modeling for surgical planning and image …

H-SegMed: A Hybrid Method for Prostate Segmentation in TRUS Images via Improved Closed Principal Curve and Improved Enhanced Machine Learning

T Peng, C Tang, Y Wu, J Cai - International Journal of …, 2022 - search.proquest.com
Prostate segmentation is an important step in prostate volume estimation, multi-modal image
registration, and patient-specific anatomical modeling for surgical planning and image …

H-SegMed: A Hybrid Method for Prostate Segmentation in TRUS Images via Improved Closed Principal Curve and Improved Enhanced Machine Learning.

T Peng, C Tang, Y Wu, J Cai - International Journal of …, 2022 - search.ebscohost.com
Prostate segmentation is an important step in prostate volume estimation, multi-modal image
registration, and patient-specific anatomical modeling for surgical planning and image …

H-SegMed: A Hybrid Method for Prostate Segmentation in TRUS Images via Improved Closed Principal Curve and Improved Enhanced Machine Learning

T Peng, C Tang, Y Wu, J Cai - International Journal of Computer Vision, 2022 - dl.acm.org
Prostate segmentation is an important step in prostate volume estimation, multi-modal image
registration, and patient-specific anatomical modeling for surgical planning and image …