Authors: Jurgen Fripp, Stuart Crozier, Simon K Warfield, S´ebastien Ourselin Source: PHYSICS IN MEDICINE AND BIOLOGY 52 (2007) 1617–1631 Speaker: Yi-Chun Ke Adviser: Bo-Chi Lai Ku-Yaw Chang

Outline Introduction Method Results Conclusion 2009/4/281

Introduction Osteoarthritis (OA) Characterized changes in the structure degeneration of the cartilage tissue Magnetic Resonance Imaging(MRI ) non-invasively 2009/4/282 patella adipose tissue tibia femur muscle tissue

Method point distribution model (PDM) 3D-statistical shape models (3D-SSM) 3D-active shape model(3D-ASM) Dice similarity coefficient(DSC) 2009/4/283

Method point distribution model (PDM) 3D-statistical shape models (3D-SSM) 3D-active shape model(3D-ASM) Dice similarity coefficient(DSC) 2009/4/284

Method point distribution model (PDM) Landmarking and obtaining correspondence Represent the shape of the bones 2009/4/285

Method point distribution model (PDM) 3D-statistical shape models (3D-SSM) 3D-active shape model(3D-ASM) Dice similarity coefficient(DSC) 2009/4/286

Method 3D-statistical shape models (3D-SSM) estimate the pose and shape individual SSM of each of the bones (patella, tibia and femur) combined knee SSM 2009/4/287 Affine

Method point distribution model (PDM) 3D-statistical shape models (3D-SSM) 3D-active shape model(3D-ASM) Dice similarity coefficient(DSC) 2009/4/288

Method 3D-active shape model(3D-ASM) two components SSM matching criteria (often an appearance model) two steps Deformation Shape restriction 2009/4/289

Method shape constraints obtained from the small database are overly restrictive Disabling shape constraints Replacing BCI > 95% 2009/4/2810 3D ASM relax

Method point distribution model (PDM) 3D-statistical shape models (3D-SSM) 3D-active shape model(3D-ASM) Dice similarity coefficient(DSC) 2009/4/2811

Method Dice similarity coefficient(DSC) sensitivity = T P /(T P + F N ) specificity = T N /(T N + F P ) Dice similarity coefficient = 2T P /(2T P + F P + F N ) 2009/4/2812 TpTp 標準答案實驗結果 FnFn FpFp TnTn

Results 2009/4/2813

Results 2009/4/2814

Conclusion automatically segment the bones and accurately extract the BCI each segmentation taking approximately 20 min DSC of 0.96,0.96 and 0.89 (femur, tibia and patella) only 3.60% failing approach for automatic use in subsequent cartilage segmentation and quantitative analysis 2009/4/2815

參考文獻 吳政容, 張顧耀, 私立大葉大學資訊工程學系, 以輻射轉換為基礎之 膝關節軟骨分割,2009 陳彥菁, 黃聖方, 私立慈濟大學醫徐資訊研究所, 應用類神經網路在 三維乳房超音波影像腫瘤之切割,2008 Jurgen Fripp, Stuart Crozier, Simon K Warfield, S´ebastien Ourselin, PHYSICS IN MEDICINE AND BIOLOGY,52,2007,1617–1631 MRI 原理 膝蓋軟骨軟化症（髕骨軟骨軟化症） Shape Model Formulation /4/2816