AIMC Topic: Image Processing, Computer-Assisted

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Dynamical Channel Pruning by Conditional Accuracy Change for Deep Neural Networks.

IEEE transactions on neural networks and learning systems
Channel pruning is an effective technique that has been widely applied to deep neural network compression. However, many existing methods prune from a pretrained model, thus resulting in repetitious pruning and fine-tuning processes. In this article,...

Deep Coattention-Based Comparator for Relative Representation Learning in Person Re-Identification.

IEEE transactions on neural networks and learning systems
Person re-identification (re-ID) favors discriminative representations over unseen shots to recognize identities in disjoint camera views. Effective methods are developed via pair-wise similarity learning to detect a fixed set of region features, whi...

Quaternion-Valued Twin-Multistate Hopfield Neural Networks With Dual Connections.

IEEE transactions on neural networks and learning systems
Dual connections (DCs) utilize the noncommutativity of quaternions and improve the noise tolerance of quaternion Hopfield neural networks (QHNNs). In this article, we introduce DCs to twin-multistate QHNNs. We conduct computer simulations to investig...

Fusion of Deep Convolutional Neural Networks for No-Reference Magnetic Resonance Image Quality Assessment.

Sensors (Basel, Switzerland)
The quality of magnetic resonance images may influence the diagnosis and subsequent treatment. Therefore, in this paper, a novel no-reference (NR) magnetic resonance image quality assessment (MRIQA) method is proposed. In the approach, deep convoluti...

Aggregation of cohorts for histopathological diagnosis with deep morphological analysis.

Scientific reports
There have been substantial efforts in using deep learning (DL) to diagnose cancer from digital images of pathology slides. Existing algorithms typically operate by training deep neural networks either specialized in specific cohorts or an aggregate ...

Reconstructing Undersampled Photoacoustic Microscopy Images Using Deep Learning.

IEEE transactions on medical imaging
One primary technical challenge in photoacoustic microscopy (PAM) is the necessary compromise between spatial resolution and imaging speed. In this study, we propose a novel application of deep learning principles to reconstruct undersampled PAM imag...

A Transfer Learning Based Super-Resolution Microscopy for Biopsy Slice Images: The Joint Methods Perspective.

IEEE/ACM transactions on computational biology and bioinformatics
Higher-resolution biopsy slice images reveal many details, which are widely used in medical practice. However, taking high-resolution slice images is more costly than taking low-resolution ones. In this paper, we propose a joint framework containing ...

Transforming UTE-mDixon MR Abdomen-Pelvis Images Into CT by Jointly Leveraging Prior Knowledge and Partial Supervision.

IEEE/ACM transactions on computational biology and bioinformatics
Computed tomography (CT) provides information for diagnosis, PET attenuation correction (AC), and radiation treatment planning (RTP). Disadvantages of CT include poor soft tissue contrast and exposure to ionizing radiation. While MRI can overcome the...

A Deep Segmentation Network of Multi-Scale Feature Fusion Based on Attention Mechanism for IVOCT Lumen Contour.

IEEE/ACM transactions on computational biology and bioinformatics
Recently, coronary heart disease has attracted more and more attention, where segmentation and analysis for vascular lumen contour are helpful for treatment. And intravascular optical coherence tomography (IVOCT) images are used to display lumen shap...

FlyIT: Drosophila Embryogenesis Image Annotation based on Image Tiling and Convolutional Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics
With the rise of image-based transcriptomics, spatial gene expression data has become increasingly important for understanding gene regulations from the tissue level down to the cell level. Especially, the gene expression images of Drosophila embryos...