AIMC Topic: Image Processing, Computer-Assisted

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A high resolution representation network with multi-path scale for retinal vessel segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Automatic retinal vessel segmentation (RVS) in fundus images is expected to be a vital step in the early image diagnosis of ophthalmologic diseases. However, it is a challenging task to detect the retinal vessel accurately ...

Recursive Deep Prior Video: A super resolution algorithm for time-lapse microscopy of organ-on-chip experiments.

Medical image analysis
Biological experiments based on organ-on-chips (OOCs) exploit light Time-Lapse Microscopy (TLM) for a direct observation of cell movement that is an observable signature of underlying biological processes. A high spatial resolution is essential to ca...

An Analysis of the Vulnerability of Two Common Deep Learning-Based Medical Image Segmentation Techniques to Model Inversion Attacks.

Sensors (Basel, Switzerland)
Recent research in computer vision has shown that original images used for training of deep learning models can be reconstructed using so-called inversion attacks. However, the feasibility of this attack type has not been investigated for complex 3D ...

Detecting pelvic fracture on 3D-CT using deep convolutional neural networks with multi-orientated slab images.

Scientific reports
Pelvic fracture is one of the leading causes of death in the elderly, carrying a high risk of death within 1 year of fracture. This study proposes an automated method to detect pelvic fractures on 3-dimensional computed tomography (3D-CT). Deep convo...

DBAN: Adversarial Network With Multi-Scale Features for Cardiac MRI Segmentation.

IEEE journal of biomedical and health informatics
With the development of medical artificial intelligence, automatic magnetic resonance image (MRI) segmentation method is quite desirable. Inspired by the power of deep neural networks, a novel deep adversarial network, dilated block adversarial netwo...

Multi-Parametric Fusion of 3D Power Doppler Ultrasound for Fetal Kidney Segmentation Using Fully Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Kidney development is key to the long-term health of the fetus. Renal volume and vascularity assessed by 3D ultrasound (3D-US) are known markers of wellbeing, however, a lack of real-time image segmentation solutions preclude these measures being use...

Graph Regularized Flow Attention Network for Video Animal Counting From Drones.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, we propose a large-scale video based animal counting dataset collected by drones (AnimalDrone) for agriculture and wildlife protection. The dataset consists of two subsets, i.e., PartA captured on site by drones and PartB collected fro...

DeepSeed Local Graph Matching for Densely Packed Cells Tracking.

IEEE/ACM transactions on computational biology and bioinformatics
The tracking of densely packed plant cells across microscopy image sequences is very challenging, because their appearance change greatly over time. A local graph matching algorithm was proposed to track such cells by exploiting the tight spatial top...

Automatic brain tumour diagnostic method based on a back propagation neural network and an extended set-membership filter.

Computer methods and programs in biomedicine
BACKGROUND: Diagnosing brain tumours remains a challenging task in clinical practice. Despite their questionable accuracy, magnetic resonance image (MRI) scans are presently considered the optimal facility for assessing the growth of tumours. However...