A method for multiple bone segmentation for three-dimensional computed tomography, the method comprising: receiving computed tomography data representing first and second bones of a patient; separately, by a processor, segmenting the first and second bones, comprising: locating voxels representing the first bone in a process and locating voxels representing the second bone in a repetition of the process, the process using different classifiers for the different bones, or estimating first and second poses of the first and second bones, the first and second poses including position and orientation and further comprising initializing first and second shapes for the first and second bones with first and second statistical shape models transformed to the first and second poses, respectively; deforming the first and second shapes as a function of the first and second statistical shape models and the CT data; refining, by the processor, the segmentation of the first bone using a first confidence map of the segmentation, the first confidence map representing a likelihood, a score or level of confidence that a given voxel indicated as being part of the first bone is part of the first bone, comprising minimizing a graph-based energy function, where the graph-based energy function comprises a unary data term as a function of the first confidence map; refining, by the processor, the segmentation of the second bone using a second confidence map of the segmentation, the second confidence map representing a likelihood, a score or level of confidence that a given voxel indicated as being part of the second bone is part of the second bone, comprising minimizing a graph-based energy function, where the graph-based map; energy function comprises a unary data term as a function of the second confidence adjusting, by the processor, the refined results of segmentation of the first and second bones jointly using the first and second confidence maps; and outputting an image showing the first and second bones with the adjusted results of the segmenting. receiving computed tomography data representing first and second bones of a patient; separately, by a processor, segmenting the first and second bones, comprising: locating voxels representing the first bone in a process and locating voxels representing the second bone in a repetition of the process, the process using different classifiers for the different bones, or estimating first and second poses of the first and second bones, the first and second poses including position and orientation and further comprising initializing first and second shapes for the first and second bones with first and second statistical shape models transformed to the first and second poses, respectively; locating voxels representing the first bone in a process and locating voxels representing the second bone in a repetition of the process, the process using different classifiers for the different bones, or estimating first and second poses of the first and second bones, the first and second poses including position and orientation and further comprising initializing first and second shapes for the first and second bones with first and second statistical shape models transformed to the first and second poses, respectively; deforming the first and second shapes as a function of the first and second statistical shape models and the CT data; refining, by the processor, the segmentation of the first bone using a first confidence map of the segmentation, the first confidence map representing a likelihood, a score or level of confidence that a given voxel indicated as being part of the first bone is part of the first bone, comprising minimizing a graph-based energy function, where the graph-based energy function comprises a unary data term as a function of the first confidence map; refining, by the processor, the segmentation of the second bone using a second confidence map of the segmentation, the second confidence map representing a likelihood, a score or level of confidence that a given voxel indicated as being part of the second bone is part of the second bone, comprising minimizing a graph-based energy function, where the graph-based map; energy function comprises a unary data term as a function of the second confidence adjusting, by the processor, the refined results of segmentation of the first and second bones jointly using the first and second confidence maps; and outputting an image showing the first and second bones with the adjusted results of the segmenting.