AIMC Topic: Image Processing, Computer-Assisted

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Fully Convolutional Network-Based Multifocus Image Fusion.

Neural computation
As the optical lenses for cameras always have limited depth of field, the captured images with the same scene are not all in focus. Multifocus image fusion is an efficient technology that can synthesize an all-in-focus image using several partially f...

Fight Recognition in video using Hough Forests and 2D Convolutional Neural Network.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
While action recognition has become an important line of research in computer vision, the recognition of particular events such as aggressive behaviors, or fights, has been relatively less studied. These tasks may be extremely useful in several video...

Prospective motion correction improves the sensitivity of fMRI pattern decoding.

Human brain mapping
We evaluated the effectiveness of prospective motion correction (PMC) on a simple visual task when no deliberate subject motion was present. The PMC system utilizes an in-bore optical camera to track an external marker attached to the participant via...

Prognostic model based on image-based time-frequency features and genetic algorithm for fetal hypoxia assessment.

Computers in biology and medicine
Cardiotocography (CTG) is applied routinely for fetal monitoring during the perinatal period to decrease the rates of neonatal mortality and morbidity as well as unnecessary interventions. The analysis of CTG traces has become an indispensable part o...

A Discrete-Time Projection Neural Network for Sparse Signal Reconstruction With Application to Face Recognition.

IEEE transactions on neural networks and learning systems
This paper deals with sparse signal reconstruction by designing a discrete-time projection neural network. Sparse signal reconstruction can be converted into an L -minimization problem, which can also be changed into the unconstrained basis pursuit d...

A supervised learning approach for diffusion MRI quality control with minimal training data.

NeuroImage
Quality control (QC) is a fundamental component of any study. Diffusion MRI has unique challenges that make manual QC particularly difficult, including a greater number of artefacts than other MR modalities and a greater volume of data. The gold stan...

Tracing cell lineages in videos of lens-free microscopy.

Medical image analysis
In vitro experiments with cultured cells are essential for studying their growth and migration pattern and thus, for gaining a better understanding of cancer progression and its treatment. Recent progress in lens-free microscopy (LFM) has rendered it...

MR Image Super-Resolution via Wide Residual Networks With Fixed Skip Connection.

IEEE journal of biomedical and health informatics
Spatial resolution is a critical imaging parameter in magnetic resonance imaging. The image super-resolution (SR) is an effective and cost efficient alternative technique to improve the spatial resolution of MR images. Over the past several years, th...

Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition.

IEEE transactions on pattern analysis and machine intelligence
Heterogeneous face recognition (HFR) aims at matching facial images acquired from different sensing modalities with mission-critical applications in forensics, security and commercial sectors. However, HFR presents more challenging issues than tradit...

Unsupervised Reverse Domain Adaptation for Synthetic Medical Images via Adversarial Training.

IEEE transactions on medical imaging
To realize the full potential of deep learning for medical imaging, large annotated datasets are required for training. Such datasets are difficult to acquire due to privacy issues, lack of experts available for annotation, underrepresentation of rar...