AIMC Topic:
Image Interpretation, Computer-Assisted
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A Markov random field approach to group-wise registration/mosaicing with application to ultrasound.
Medical image analysis
Jun 3, 2015
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...
Female
Reproducibility of Results
Sensitivity and Specificity
Ultrasonography
Algorithms
Computer Simulation
Pregnancy
Image Interpretation, Computer-Assisted
Pattern Recognition, Automated
Humans
Image Enhancement
Machine Learning
Subtraction Technique
Imaging, Three-Dimensional
Models, Statistical
Data Interpretation, Statistical
Markov Chains
A Robust and Fast Computation Touchless Palm Print Recognition System Using LHEAT and the IFkNCN Classifier.
Computational intelligence and neuroscience
May 31, 2015
Mobile implementation is a current trend in biometric design. This paper proposes a new approach to palm print recognition, in which smart phones are used to capture palm print images at a distance. A touchless system was developed because of public ...
Combined unsupervised-supervised classification of multiparametric PET/MRI data: application to prostate cancer.
NMR in biomedicine
May 26, 2015
Multiparametric medical imaging data can be large and are often complex. Machine learning algorithms can assist in image interpretation when reliable training data exist. In most cases, however, knowledge about ground truth (e.g. histology) and thus ...
Prostatic Neoplasms
Positron-Emission Tomography
Image Interpretation, Computer-Assisted
Pattern Recognition, Automated
Middle Aged
Magnetic Resonance Imaging
Multimodal Imaging
Image Enhancement
Machine Learning
Algorithms
Reproducibility of Results
Aged
Aged, 80 and over
Sensitivity and Specificity
Male
Humans
Echocardiogram enhancement using supervised manifold denoising.
Medical image analysis
May 21, 2015
This paper presents data-driven methods for echocardiogram enhancement. Existing denoising algorithms typically rely on a single noise model, and do not generalize to the composite noise sources typically found in real-world echocardiograms. Our meth...
Automated extraction and labelling of the arterial tree from whole-body MRA data.
Medical image analysis
May 21, 2015
In this work, we present a fully automated algorithm for extraction of the 3D arterial tree and labelling the tree segments from whole-body magnetic resonance angiography (WB-MRA) sequences. The algorithm developed consists of two core parts (i) 3D v...
Polyp Detection via Imbalanced Learning and Discriminative Feature Learning.
IEEE transactions on medical imaging
May 18, 2015
Recent achievement of the learning-based classification leads to the noticeable performance improvement in automatic polyp detection. Here, building large good datasets is very crucial for learning a reliable detector. However, it is practically chal...
MR image synthesis by contrast learning on neighborhood ensembles.
Medical image analysis
May 18, 2015
Automatic processing of magnetic resonance images is a vital part of neuroscience research. Yet even the best and most widely used medical image processing methods will not produce consistent results when their input images are acquired with differen...
Developing an Intelligent Automatic Appendix Extraction Method from Ultrasonography Based on Fuzzy ART and Image Processing.
Computational and mathematical methods in medicine
May 18, 2015
Ultrasound examination (US) does a key role in the diagnosis and management of the patients with clinically suspected appendicitis which is the most common abdominal surgical emergency. Among the various sonographic findings of appendicitis, outer di...
Log-Spiral Keypoint: A Robust Approach toward Image Patch Matching.
Computational intelligence and neuroscience
May 5, 2015
Matching of keypoints across image patches forms the basis of computer vision applications, such as object detection, recognition, and tracking in real-world images. Most of keypoint methods are mainly used to match the high-resolution images, which ...
A Robust Deep Model for Improved Classification of AD/MCI Patients.
IEEE journal of biomedical and health informatics
May 4, 2015
Accurate classification of Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI), plays a critical role in possibly preventing progression of memory impairment and improving quality of life for AD patients. Among many rese...
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