Lumbar and Thoracic Spine Segmentation Using a Statistical Multi-object Shape$$+$$Pose Model

Alexander Seitel; Abtin Rasoulian; Robert Rohling; Purang Abolmaesumi

doi:10.1007/978-3-319-14148-0_19

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Lumbar and Thoracic Spine Segmentation Using a Statistical Multi-object Shape$$+$$Pose Model

Alexander Seitel Abtin Rasoulian Robert Rohling Purang Abolmaesumi

Year: 2015 Lecture notes in computational vision and biomechanics Pages: 221-225 Publisher: Springer International Publishing

DOI: 10.1007/978-3-319-14148-0_19

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Keywords:

Segmentation Artificial intelligence Sørensen–Dice coefficient Computer science Object (grammar) Flexibility (engineering) Computer vision Vertebral column Scale-space segmentation Image segmentation Pattern recognition (psychology) Medicine Mathematics Anatomy Statistics

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Medical Imaging and Analysis

Physical Sciences → Engineering → Biomedical Engineering

Dental Radiography and Imaging

Health Sciences → Dentistry → Oral Surgery

Spinal Fractures and Fixation Techniques

Health Sciences → Medicine → Surgery

Lumbar and Thoracic Spine Segmentation Using a Statistical Multi-object Shape$$+$$Pose Model

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