AIMC Topic: Subtraction Technique

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Weighting training images by maximizing distribution similarity for supervised segmentation across scanners.

Medical image analysis
Many automatic segmentation methods are based on supervised machine learning. Such methods have proven to perform well, on the condition that they are trained on a sufficiently large manually labeled training set that is representative of the images ...

A Markov random field approach to group-wise registration/mosaicing with application to ultrasound.

Medical image analysis
In this paper we present a group-wise non-rigid registration/mosaicing algorithm based on block-matching, which is developed within a probabilistic framework. The discrete form of its energy functional is linked to a Markov Random Field (MRF) contain...

Online kernel slow feature analysis for temporal video segmentation and tracking.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Slow feature analysis (SFA) is a dimensionality reduction technique which has been linked to how visual brain cells work. In recent years, the SFA was adopted for computer vision tasks. In this paper, we propose an exact kernel SFA (KSFA) framework f...

Robust representation and recognition of facial emotions using extreme sparse learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Recognition of natural emotions from human faces is an interesting topic with a wide range of potential applications, such as human-computer interaction, automated tutoring systems, image and video retrieval, smart environments, and driver warning sy...

Structured patch model for a unified automatic and interactive segmentation framework.

Medical image analysis
We present a novel interactive segmentation framework incorporating a priori knowledge learned from training data. The knowledge is learned as a structured patch model (StPM) comprising sets of corresponding local patch priors and their pairwise spat...

Selective invocation of shape priors for deformable segmentation and morphologic classification of prostate cancer tissue microarrays.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Shape based active contours have emerged as a natural solution to overlap resolution. However, most of these shape-based methods are computationally expensive. There are instances in an image where no overlapping objects are present and applying thes...

Feature selection in supervised saliency prediction.

IEEE transactions on cybernetics
There is an increasing interest in learning mappings from features to saliency maps based on human fixation data on natural images. These models have achieved better results than most bottom-up (unsupervised) saliency models. However, they usually us...

3-D model-based tracking for UAV indoor localization.

IEEE transactions on cybernetics
This paper proposes a novel model-based tracking approach for 3-D localization. One main difficulty of standard model-based approach lies in the presence of low-level ambiguities between different edges. In this paper, given a 3-D model of the edges ...

Multimodal medical information retrieval with unsupervised rank fusion.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Modern medical information retrieval systems are paramount to manage the insurmountable quantities of clinical data. These systems empower health care experts in the diagnosis of patients and play an important role in the clinical decision process. H...

Comparing fusion techniques for the ImageCLEF 2013 medical case retrieval task.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Retrieval systems can supply similar cases with a proven diagnosis to a new example case under observation to help clinicians during their work. The ImageCLEFmed evaluation campaign proposes a framework where research groups can compare case-based re...