Developmental　dysplasia　of　the　hip　is　a　congenital　hip　joint　malformation　affecting　the　proximal　femurs　and　acetabulum　that　are　subluxatable,　dislocatable,　and　dislocated.　Conventionally,　physicians　made　diagnoses　and　treatments　only　based　on　findings　from　two-dimensional　(2D)　images　by　manually　calculating　clinic　parameters.　However,　anatomical　complexity　of　the　disease　and　the　limitation　of　current　standard　procedures　make　accurate　diagnosis　quite　difficultly.　In　this　study,　we　developed　a　system　that　provides　quantitative　measurement　of　3D　clinical　indexes　based　on　computed　tomography　(CT)　images.　To　extract　bone　structure　from　surrounding　tissues　more　accurately,　the　system　firstly　segments　the　bone　using　a　knowledge-based　fuzzy　clustering　method,　which　is　formulated　by　modifying　the　objective　function　of　the　standard　fuzzy　c-means　algorithm　with　additive　adaptation　penalty.　The　second　part　of　the　system　calculates　automatically　the　clinical　indexes,　which　are　extended　from　2D　to　3D　for　accurate　description　of　spatial　relationship　between　femurs　and　acetabulum.　To　evaluate　the　system　performance,　experimental　study　based　on　22　patients　with　unilateral　or　bilateral　affected　hip　was　performed.　The　results　of　3D　acetabulum　index　(AI)　automatically　provided　by　the　system　were　validated　by　comparison　with　2D　results　measured　by　surgeons　manually.　The　correlation　between　the　two　results　was　found　to　be　0.622　(p0.01).©2009　SPIE.