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This paper presents feature-based morphometry (FBM), a new fully data-driven technique for discovering patterns of group-related anatomical structure in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between subjects, FBM explicitly aims to identify distinctive anatomical patterns that may only be present(More)
This paper presents a novel framework for detecting, localizing, and classifying faces in terms of visual traits, e.g., sex or age, from arbitrary viewpoints and in the presence of occlusion. All three tasks are embedded in a general viewpoint-invariant model of object class appearance derived from local scale-invariant features, where features are(More)
This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized(More)
This paper investigates ordinal image description for invariant feature correspondence. Ordinal description is a meta-technique which considers image measurements in terms of their ranks in a sorted array, instead of the measurement values themselves. Rank-ordering normalizes descriptors in a manner invariant under monotonic deformations of the underlying(More)
We present an image segmentation method that transfers label maps of entire organs from the training images to the novel image to be segmented. The transfer is based on sparse correspondences between keypoints that represent automatically identified distinctive image locations. Our segmentation algorithm consists of three steps: (i) keypoint matching, (ii)(More)
BACKGROUND This study is aimed to determine whether anxiety disorders are associated with suicide attempts with intent to die and to further investigate the characteristics of deliberate self-harm (DSH) among anxiety disorders. METHOD Data came from the Collaborative Psychiatric Epidemiological Surveys (N = 20,130; age 18 years and older; response rate =(More)
In this paper, we present a statistical parts-based model (PBM) of appearance, applied to the problem of modeling intersubject anatomical variability in magnetic resonance (MR) brain images. In contrast to global image models such as the active appearance model (AAM), the PBM consists of a collection of localized image regions, referred to as parts, whose(More)
The fundamental matrix (FM) represents the perspective transform between two or more uncalibrated images of a stationary scene, and is traditionally estimated based on 2-parameter point-to-point correspondences between image pairs. Recent invariant correspondence techniques however , provide robust correspondences in terms of 4 to 6-parameter invariant(More)
Image similarity measures for registration can be considered within the general context of joint intensity histograms, which consist of bin count parameters estimated from image intensity samples. Many approaches to estimation are ML (maximum likelihood), which tends to be unstable in the presence sparse data, resulting in registration that is driven by(More)