Journals starting with mlm

MLMI11 * *Machine Learning in Medical Imaging
* 3D Segmentation in CT Imagery with Conditional Random Fields and Histograms of Oriented Gradients
* Accurate Regression-Based 4D Mitral Valve Surface Reconstruction from 2D+t MRI Slices
* Anatomical Regularization on Statistical Manifolds for the Classification of Patients with Alzheimer's Disease
* Automated Cephalometric Landmark Localization Using Sparse Shape and Appearance Models
* Automated Detection of Major Thoracic Structures with a Novel Online Learning Method
* Automated Identification of Thoracolumbar Vertebrae Using Orthogonal Matching Pursuit
* Automated Nuclear Segmentation of Coherent Anti-Stokes Raman Scattering Microscopy Images by Coupling Superpixel Context Information with Artificial Neural Networks
* Automated Selection of Standardized Planes from Ultrasound Volume
* Automatic Human Knee Cartilage Segmentation from Multi-contrast MR Images Using Extreme Learning Machines and Discriminative Random Fields
* Automatic Morphological Classification of Lung Cancer Subtypes with Boosting Algorithms for Optimizing Therapy
* Automatic Segmentation of Vertebrae from Radiographs: A Sample-Driven Active Shape Model Approach
* Classifying Small Lesions on Breast MRI through Dynamic Enhancement Pattern Characterization
* Comparison Study of Inferences on Graphical Model for Registering Surface Model to 3D Image, A
* Computer-Aided Detection of Polyps in CT Colonography with Pixel-Based Machine Learning Techniques
* Computer-Assisted Intramedullary Nailing Using Real-Time Bone Detection in 2D Ultrasound Images
* DCE-MRI Analysis Using Sparse Adaptive Representations
* Directed Graph Based Image Registration
* Effective Supervised Framework for Retinal Blood Vessel Segmentation Using Local Standardisation and Bagging, An
* Faster Segmentation Algorithm for Optical Coherence Tomography Images with Guaranteed Smoothness
* Fuzzy Statistical Unsupervised Learning Based Total Lesion Metabolic Activity Estimation in Positron Emission Tomography Images
* Hot Spots Conjecture and Its Application to Modeling Tubular Structures
* Improving the Classification Accuracy of the Classic RF Method by Intelligent Feature Selection and Weighted Voting of Trees with Application to Medical Image Segmentation
* Large-Scale Manifold Learning Approach for Brain Tumor Progression Prediction, A
* Learning Optical Flow Propagation Strategies Using Random Forests for Fast Segmentation in Dynamic 2D and 3D Echocardiography
* Learning Statistical Correlation of Prostate Deformations for Fast Registration
* Locally Deformable Statistical Shape Model, A
* Machine Learning Approach to Tongue Motion Analysis in 2D Ultrasound Image Sequences, A
* Maximum Likelihood and James-Stein Edge Estimators for Left Ventricle Tracking in 3D Echocardiography
* Monte Carlo Expectation Maximization with Hidden Markov Models to Detect Functional Networks in Resting-State fMRI
* Multi-Kernel Classification for Integration of Clinical and Imaging Data: Application to Prediction of Cognitive Decline in Older Adults
* MultiCost: Multi-stage Cost-sensitive Classification of Alzheimer's Disease
* Network-Based Classification Using Cortical Thickness of AD Patients
* Non-rigid Registration Framework That Accommodates Pathology Detection, A
* Predicting Clinical Scores Using Semi-supervised Multimodal Relevance Vector Regression
* Probabilistic Graphical Model of SPECT/MRI
* Random Forest-Based Manifold Learning for Classification of Imaging Data in Dementia
* Rapidly Adaptive Cell Detection Using Transfer Learning with a Global Parameter
* Segmentation Based Features for Lymph Node Detection from 3-D Chest CT
* Segmentation of Skull Base Tumors from MRI Using a Hybrid Support Vector Machine-Based Method
* Segmenting Hippocampus from 7.0 Tesla MR Images by Combining Multiple Atlases and Auto-Context Models
* Spatial Nonparametric Mixed-Effects Model with Spatial-Varying Coefficients for Analysis of Populations
* Subject-Specific Cardiac Segmentation Based on Reinforcement Learning with Shape Instantiation
* Texture Analysis by a PLS Based Method for Combined Feature Extraction and Selection
* Tree Structured Model of Skin Lesion Growth Pattern via Color Based Cluster Analysis
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MLMI12 * *Machine Learning in Medical Imaging
* Biomedical Images Classification by Universal Nearest Neighbours Classifier Using Posterior Probability
* Cardiac LV and RV Segmentation Using Mutual Context Information
* Combining Multiple Image Segmentations by Maximizing Expert Agreement
* Computer Aided Skin Lesion Diagnosis with Humans in the Loop
* Computer-Aided Detection of Aneurysms in 3D Time-of-Flight MRA Datasets
* Data Driven Constraints for the SVM
* Dense Deformation Reconstruction via Sparse Coding
* Description and Classification of Confocal Endomicroscopic Images for the Automatic Diagnosis of Inflammatory Bowel Disease
* Finding Deformable Shapes by Correspondence-Free Instantiation and Registration of Statistical Shape Models
* Gradient Projection Learning for Parametric Nonrigid Registration
* Graph-Based Inter-subject Classification of Local fMRI Patterns
* Group Sparsity Constrained Automatic Brain Label Propagation
* Hierarchical Ensemble of Multi-level Classifiers for Diagnosis of Alzheimer's Disease
* Human Age Estimation with Surface-Based Features from MRI Images
* Integrating Statistical Shape Models into a Graph Cut Framework for Tooth Segmentation
* Learning Correspondences in Knee MR Images from the Osteoarthritis Initiative
* Learning to Locate Cortical Bone in MRI
* Learning to Rank from Medical Imaging Data
* Localized MKL Method for Brain Classification with Known Intra-class Variability, A
* Model-Driven Centerline Extraction for Severely Occluded Major Coronary Arteries
* MRI Confirmed Prostate Tissue Classification with Laplacian Eigenmaps of Ultrasound RF Spectra
* Non-parametric Density Modeling and Outlier-Detection in Medical Imaging Datasets
* Nonlinear Discriminant Graph Embeddings for Detecting White Matter Lesions in FLAIR MRI
* Novel 3D Joint MGRF Framework for Precise Lung Segmentation, A
* On the Creation of Generic fMRI Feature Networks Using 3-D Moment Invariants
* Quality Classification of Microscopic Imagery with Weakly Supervised Learning
* Random Forest Based Approach for One Class Classification in Medical Imaging, A
* Simultaneous Registration and Segmentation by L1 Minimization
* Sparse Patch-Guided Deformation Estimation for Improved Image Registration
* Supervised Image Segmentation across Scanner Protocols: A Transfer Learning Approach
* Towards Improving the Accuracy of Sensorless Freehand 3D Ultrasound by Learning
* Transductive Prostate Segmentation for CT Image Guided Radiotherapy
* Use of Pattern-Information Analysis in Vision Science: A Pragmatic Examination
34 for MLMI12

MLMI14 * *Machine Learning in Medical Imaging
* 3D Intervertebral Disc Localization and Segmentation from MR Images by Data-Driven Regression and Classification
* Anatomically Constrained Weak Classifier Fusion for Early Detection of Alzheimer's Disease
* Automatic Bone and Marrow Extraction from Dual Energy CT through SVM Margin-Based Multi-Material Decomposition Model Selection
* Colon Biopsy Classification Using Crypt Architecture
* Constrained Regression Forests Solution to 3D Fetal Ultrasound Plane Localization for Longitudinal Analysis of Brain Growth and Maturation, A
* Context-Aware Anatomical Landmark Detection: Application to Deformable Model Initialization in Prostate CT Images
* Deep Learning Based Automatic Immune Cell Detection for Immunohistochemistry Images
* Deep Learning for Cerebellar Ataxia Classification and Functional Score Regression
* Deep Learning of Image Features from Unlabeled Data for Multiple Sclerosis Lesion Segmentation
* Deformation Field Correction for Spatial Normalization of PET Images Using a Population-Derived Partial Least Squares Model
* Detection of Mammographic Masses by Content-Based Image Retrieval
* Exploring Compact Representation of SICE Matrices for Functional Brain Network Classification
* Feature Selection Based on SVM Significance Maps for Classification of Dementia
* Fetal Abdominal Standard Plane Localization through Representation Learning with Knowledge Transfer
* Geodesic Geometric Mean of Regional Covariance Descriptors as an Image-Level Descriptor for Nuclear Atypia Grading in Breast Histology Images
* Gleason Grading of Prostate Tumours with Max-Margin Conditional Random Fields
* Graph-Based Label Propagation in Fetal Brain MR Images
* Improved Reproducibility of Neuroanatomical Definitions through Diffeomorphometry and Complexity Reduction
* In Vivo MRI Based Prostate Cancer Identification with Random Forests and Auto-context Model
* Inferring Sources of Dementia Progression with Network Diffusion Model
* Interactive Prostate Segmentation Based on Adaptive Feature Selection and Manifold Regularization
* Learning Distance Transform for Boundary Detection and Deformable Segmentation in CT Prostate Images
* Learning of Atlas Forest Hierarchy for Automatic Labeling of MR Brain Images
* Manifold Alignment and Transfer Learning for Classification of Alzheimer's Disease
* Multi-atlas Segmentation with Learning-Based Label Fusion
* Network-Guided Group Feature Selection for Classification of Autism Spectrum Disorder
* Novel Multi-Atlas Segmentation by Matrix Completion
* Online Discriminative Multi-atlas Learning for Isointense Infant Brain Segmentation
* Optimal MAP Parameters Estimation in STAPLE: Learning from Performance Parameters versus Image Similarity Information
* Persistent Reeb Graph Matching for Fast Brain Search
* Prediction of Standard-Dose PET Image by Low-Dose PET and MRI Images
* Robust Deep Learning for Improved Classification of AD/MCI Patients
* Searching for Structures of Interest in an Ultrasound Video Sequence
* Solutions for Missing Parameters in Computer-Aided Diagnosis with Multiparametric Imaging Data
* Sparse Discriminative Feature Selection for Multi-class Alzheimer's Disease Classification
* Sparsity-Learning-Based Longitudinal MR Image Registration for Early Brain Development
* Stacked Multiscale Feature Learning for Domain Independent Medical Image Segmentation
* Structured Random Forests for Myocardium Delineation in 3D Echocardiography
* Subject Specific Sparse Dictionary Learning for Atlas Based Brain MRI Segmentation
* Topological Descriptors of Histology Images
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MLMI15 * *Machine Learning in Medical Imaging
* Automatic Detection of Good/Bad Colonies of iPS Cells Using Local Features
* Boosting Convolutional Filters with Entropy Sampling for Optic Cup and Disc Image Segmentation from Fundus Images
* Brain Fiber Clustering Using Non-negative Kernelized Matching Pursuit
* BundleMAP: Anatomically Localized Features from dMRI for Detection of Disease
* Clustering Analysis for Semi-supervised Learning Improves Classification Performance of Digital Pathology
* Composite of Features for Learning-Based Coronary Artery Segmentation on Cardiac CT Angiography, A
* Computer-Assisted Diagnosis of Lung Cancer Using Quantitative Topology Features
* Craniomaxillofacial Deformity Correction via Sparse Representation in Coherent Space
* Deep Learning, Sparse Coding, and SVM for Melanoma Recognition in Dermoscopy Images
* Detecting Abnormal Cell Division Patterns in Early Stage Human Embryo Development
* Ensemble Prostate Tumor Classification in H&E Whole Slide Imaging via Stain Normalization and Cell Density Estimation
* FADR: Functional-Anatomical Discriminative Regions for Rest fMRI Characterization
* Flexible and Latent Structured Output Learning, Application to Histology
* Group-Constrained Laplacian Eigenmaps: Longitudinal AD Biomarker Learning
* HEp-2 Staining Pattern Recognition Using Stacked Fisher Network for Encoding Weber Local Descriptor
* Hierarchical Multi-modal Image Registration by Learning Common Feature Representations
* Identification of Infants at Risk for Autism Using Multi-parameter Hierarchical White Matter Connectomes
* Identifying Abnormal Network Alterations Common to Traumatic Brain Injury and Alzheimer's Disease Patients Using Functional Connectome Data
* Inherent Structure-Guided Multi-view Learning for Alzheimer's Disease and Mild Cognitive Impairment Classification
* Joint Learning of Multiple Longitudinal Prediction Models by Exploring Internal Relations
* Learning and Combining Image Similarities for Neonatal Brain Population Studies
* Longitudinal Patch-Based Segmentation of Multiple Sclerosis White Matter Lesions
* Machine Learning on High Dimensional Shape Data from Subcortical Brain Surfaces: A Comparison of Feature Selection and Classification Methods
* Multi-atlas Context Forests for Knee MR Image Segmentation
* Multi-source Information Gain for Random Forest: An Application to CT Image Prediction from MRI Data
* Multi-view Classification for Identification of Alzheimer's Disease
* Multimodal Multi-label Transfer Learning for Early Diagnosis of Alzheimer's Disease
* New Image Data Set and Benchmark for Cervical Dysplasia Classification Evaluation, A
* Node-Based Gaussian Graphical Model for Identifying Discriminative Brain Regions from Connectivity Graphs
* Non-rigid Free-Form 2D-3D Registration Using Statistical Deformation Model
* Nonlinear Feature Transformation and Deep Fusion for Alzheimer's Disease Staging Analysis
* Nonlinear Graph Fusion for Multi-modal Classification of Alzheimer's Disease
* Predicting Standard-Dose PET Image from Low-Dose PET and Multimodal MR Images Using Mapping-Based Sparse Representation
* Segmentation of Right Ventricle in Cardiac MR Images Using Shape Regression
* Semi-automatic Liver Tumor Segmentation in Dynamic Contrast-Enhanced CT Scans Using Random Forests and Supervoxels
* Soft-Split Random Forest for Anatomy Labeling
* Soft-Split Sparse Regression Based Random Forest for Predicting Future Clinical Scores of Alzheimer's Disease
* Supervoxel Classification Forests for Estimating Pairwise Image Correspondences
* Tumor Classification by Deep Polynomial Network and Multiple Kernel Learning on Small Ultrasound Image Dataset
* Visual Saliency Based Active Learning for Prostate MRI Segmentation
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MLMI16 * *Machine Learning in Medical Imaging
* Automated 3D Ultrasound Biometry Planes Extraction for First Trimester Fetal Assessment
* Automatic Hippocampal Subfield Segmentation from 3T Multi-modality Images
* Bilateral Regularization in Reproducing Kernel Hilbert Spaces for Discontinuity Preserving Image Registration
* Building an Ensemble of Complementary Segmentation Methods by Exploiting Probabilistic Estimates
* Comparison of Multi-resolution Analysis Patterns for Texture Classification of Breast Tumors Based on DCE-MRI
* Cross-Modality Anatomical Landmark Detection Using Histograms of Unsigned Gradient Orientations and Atlas Location Autocontext
* Deep Ensemble Sparse Regression Network for Alzheimer's Disease Diagnosis
* Detecting Osteophytes in Radiographs of the Knee to Diagnose Osteoarthritis
* Direct Estimation of Fiber Orientations Using Deep Learning in Diffusion Imaging
* Do We Need Large Annotated Training Data for Detection Applications in Biomedical Imaging? A Case Study in Renal Glomeruli Detection
* Dual-Layer Groupwise Registration for Consistent Labeling of Longitudinal Brain Images
* Fast Neuroimaging-Based Retrieval for Alzheimer's Disease Analysis
* Functional Connectivity Network Fusion with Dynamic Thresholding for MCI Diagnosis
* Identifying High Order Brain Connectome Biomarkers via Learning on Hypergraph
* Improving Single-Modal Neuroimaging Based Diagnosis of Brain Disorders via Boosted Privileged Information Learning Framework
* Iterative Dual LDA: A Novel Classification Algorithm for Resting State fMRI
* Joint Discriminative and Representative Feature Selection for Alzheimer's Disease Diagnosis
* Learning Appearance and Shape Evolution for Infant Image Registration in the First Year of Life
* Learning for Graph-Based Sensorless Freehand 3D Ultrasound
* Learning Global and Cluster-Specific Classifiers for Robust Brain Extraction in MR Data
* Learning Representation for Histopathological Image with Quaternion Grassmann Average Network
* Learning-Based 3T Brain MRI Segmentation with Guidance from 7T MRI Labeling
* Mitosis Detection in Intestinal Crypt Images with Hough Forest and Conditional Random Fields
* Multi-label Deep Regression and Unordered Pooling for Holistic Interstitial Lung Disease Pattern Detection
* Multi-resolution-Tract CNN with Hybrid Pretrained and Skin-Lesion Trained Layers
* Novel Morphological Features for Non-mass-like Breast Lesion Classification on DCE-MRI
* Patch-Based Hippocampus Segmentation Using a Local Subspace Learning Method
* Regression Guided Deformable Models for Segmentation of Multiple Brain ROIs
* Retinal Image Quality Classification Using Saliency Maps and CNNs
* Segmentation of Perivascular Spaces Using Vascular Features and Structured Random Forest from 7T MR Image
* Segmentation-Free Estimation of Kidney Volumes in CT with Dual Regression Forests
* Semi-supervised Large Margin Algorithm for White Matter Hyperintensity Segmentation, A
* Sparse Coding Based Skin Lesion Segmentation Using Dynamic Rule-Based Refinement
* Structure Fusion for Automatic Segmentation of Left Atrial Aneurysm Based on Deep Residual Networks
* Transductive Maximum Margin Classification of ADHD Using Resting State fMRI
* Tree-Based Transforms for Privileged Learning
* Tumor Lesion Segmentation from 3D PET Using a Machine Learning Driven Active Surface
* Unsupervised Discovery of Emphysema Subtypes in a Large Clinical Cohort
39 for MLMI16

MLMotion08 * *Machine Learning for Vision-based Motion Analysis
* Approximate RBF kernel SVM and its applications in pedestrian classification
* Capturing Video Structure with Mixture of Probabilistic Index Maps
* Combination of supervised and unsupervised methods for navigation path mining
* Facial motion analysis using clustered shortest path tree registration
* Flexible dictionaries for action classification
* framework for indexing human actions in video, A
* From learning individual actions to 3D animation of team sports
* From local temporal correlation to global anomaly detection
* Human motion tracking using a color-based particle filter driven by optical flow
* Independent viewpoint silhouette-based human action modeling and recognition
* Learning Bayesian tracking for motion estimation
* Learning Pullback metrics for linear models
* Linear and Non-Linear Models for Monocular 3D Motion Capture
* new spatio-temporal MRF framework for video-based object segmentation, A
* Optimizing trajectories clustering for activity recognition
* Self-similar regularization of optic-flow for turbulent motion estimation
* Simultaneous learning of motion and appearance
* Spatio-temporal feature recognition using randomised Ferns
* Spatio-temporal motion pattern modeling of extremely crowded scenes
* Super-resolved digests of humans in video
* Unsupervised learning of behavioural patterns for video-surveillance
22 for MLMotion08

MLMotion09 * *Machine Learning for Vision-based Motion Analysis
* Action exemplar based real-time action detection
* Combining discriminative appearance and segmentation cues for articulated human pose estimation
* Evaluation of threshold model HMMS and Conditional Random Fields for recognition of spatiotemporal gestures in sign language
* Fitting parametric road models to spatio-temporal derivatives
* H-APF: Using hierarchical representation of human body for 3-D articulated tracking and action classification
* Human action recognition from a single clip per action
* improved local descriptor and threshold learning for unsupervised dynamic texture segmentation, An
* Learning mixed-state Markov models for statistical motion texture tracking
* On-line learning of the transition model for Recursive Bayesian Estimation
* Randomized algorithm of spectral clustering and image/video segmentation using a minority of pixels
* Sparse learning approach to the problem of robust estimation of camera locations
* Supervised Neighborhood Topology Learning for Human Action Recognition
* Two-layer generative models for estimating unknown gait kinematics
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Last update:28-Nov-16 20:52:40
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