Adam C. Hodge
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Adam C. Hodge has a total of 1 co-authors. Here are the top co-authors by number of shared publications:
- Hanif M. Ladak
Department of Otolaryngology-Head and Neck Surgery, Western University, London, Canada
2 shared publications
Latest Publications
- 1 August 2006
- Published by Institute of Electrical and Electronics Engineers (IEEE) in 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
- Vol. 2006 (1557170X) , 2337-2340
3D Prostate Boundary Segmentation From Ultrasound Images Using 2D Active Shape Models
Boundary outlining, or segmentation, of the prostate is an important task in diagnosis and treatment planning for prostate cancer. This paper describes an algorithm for semi-automatic, three-dimensional (3D) segmentation of the prostate boundary from ultrasound images based on two-dimensional (2D) active shape models (ASM) and rotation-based slicing. Evaluation of the algorithm used distance- and volume-based error metrics to compare algorithm generated boundary outlines to gold standard (manually generated) boundary outlines. The mean absolute distance between the algorithm and gold standard boundaries was 1.09plusmn0.49 mm, the average percent absolute volume difference was 3.28plusmn3.16%, and a 5x speed increase as compared manual planimetry was achieved
- 1 August 2006
- Published by Institute of Electrical and Electronics Engineers (IEEE) in 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
- Vol. 2006 (1557170X) , 2337-2340
3D Prostate Boundary Segmentation From Ultrasound Images Using 2D Active Shape Models
Boundary outlining, or segmentation, of the prostate is an important task in diagnosis and treatment planning for prostate cancer. This paper describes an algorithm for semi-automatic, three-dimensional (3D) segmentation of the prostate boundary from ultrasound images based on two-dimensional (2D) active shape models (ASM) and rotation-based slicing. Evaluation of the algorithm used distance- and volume-based error metrics to compare algorithm generated boundary outlines to gold standard (manually generated) boundary outlines. The mean absolute distance between the algorithm and gold standard boundaries was 1.09plusmn0.49 mm, the average percent absolute volume difference was 3.28plusmn3.16%, and a 5x speed increase as compared manual planimetry was achieved
- 1 August 2006
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 1557170X,p. 2337-2340
3D Prostate Boundary Segmentation From Ultrasound Images Using 2D Active Shape Models
Boundary outlining, or segmentation, of the prostate is an important task in diagnosis and treatment planning for prostate cancer. This paper describes an algorithm for semi-automatic, three-dimensional (3D) segmentation of the prostate boundary from ultrasound images based on two-dimensional (2D) active shape models (ASM) and rotation-based slicing. Evaluation of the algorithm used distance- and volume-based error metrics to compare algorithm generated boundary outlines to gold standard (manually generated) boundary outlines. The mean absolute distance between the algorithm and gold standard boundaries was 1.09plusmn0.49 mm, the average percent absolute volume difference was 3.28plusmn3.16%, and a 5x speed increase as compared manual planimetry was achieved
- 1 August 2006
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 1557170X,p. 2337-2340
3D Prostate Boundary Segmentation From Ultrasound Images Using 2D Active Shape Models
Boundary outlining, or segmentation, of the prostate is an important task in diagnosis and treatment planning for prostate cancer. This paper describes an algorithm for semi-automatic, three-dimensional (3D) segmentation of the prostate boundary from ultrasound images based on two-dimensional (2D) active shape models (ASM) and rotation-based slicing. Evaluation of the algorithm used distance- and volume-based error metrics to compare algorithm generated boundary outlines to gold standard (manually generated) boundary outlines. The mean absolute distance between the algorithm and gold standard boundaries was 1.09plusmn0.49 mm, the average percent absolute volume difference was 3.28plusmn3.16%, and a 5x speed increase as compared manual planimetry was achieved