AIMC Topic: Image Processing, Computer-Assisted

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A Deep Learning-based Method to Extract Lumen and Media-Adventitia in Intravascular Ultrasound Images.

Ultrasonic imaging
Intravascular ultrasound (IVUS) imaging allows direct visualization of the coronary vessel wall and is suitable for assessing atherosclerosis and the degree of stenosis. Accurate segmentation and lumen and median-adventitia (MA) measurements from IVU...

Stacked dilated convolutions and asymmetric architecture for U-Net-based medical image segmentation.

Computers in biology and medicine
Deep learning has been widely utilized for medical image segmentation. The most commonly used U-Net and its variants often share two common characteristics but lack solid evidence for the effectiveness. First, each block (i.e., consecutive convolutio...

Deep convolutional neural network-based automated segmentation of the maxillofacial complex from cone-beam computed tomography:A validation study.

Journal of dentistry
OBJECTIVES: The present study investigated the accuracy, consistency, and time-efficiency of a novel deep convolutional neural network (CNN) based model for the automated maxillofacial bone segmentation from cone beam computed tomography (CBCT) image...

EIEN: Endoscopic Image Enhancement Network Based on Retinex Theory.

Sensors (Basel, Switzerland)
In recent years, deep convolutional neural network (CNN)-based image enhancement has shown outstanding performance. However, due to the problems of uneven illumination and low contrast existing in endoscopic images, the implementation of medical endo...

Fall Detection for Shipboard Seafarers Based on Optimized BlazePose and LSTM.

Sensors (Basel, Switzerland)
Aiming to avoid personal injury caused by the failure of timely medical assistance following a fall by seafarer members working on ships, research on the detection of seafarer's falls and timely warnings to safety officers can reduce the loss and sev...

Marker-controlled watershed with deep edge emphasis and optimized H-minima transform for automatic segmentation of densely cultivated 3D cell nuclei.

BMC bioinformatics
BACKGROUND: The segmentation of 3D cell nuclei is essential in many tasks, such as targeted molecular radiotherapies (MRT) for metastatic tumours, toxicity screening, and the observation of proliferating cells. In recent years, one popular method for...

Multiscale segmentation- and error-guided iterative convolutional neural network for cerebral neuron segmentation in microscopic images.

Microscopy research and technique
This article uses microscopy images obtained from diverse anatomical regions of macaque brain for neuron semantic segmentation. The complex structure of brain, the large intra-class staining intensity difference within neuron class, the small inter-c...

Infrared and Visible Image Fusion Method Using Salience Detection and Convolutional Neural Network.

Sensors (Basel, Switzerland)
This paper presents an algorithm for infrared and visible image fusion using significance detection and Convolutional Neural Networks with the aim of integrating discriminatory features and improving the overall quality of visual perception. Firstly,...

Quantitative evaluation of a deep learning-based framework to generate whole-body attenuation maps using LSO background radiation in long axial FOV PET scanners.

European journal of nuclear medicine and molecular imaging
PURPOSE: Attenuation correction is a critically important step in data correction in positron emission tomography (PET) image formation. The current standard method involves conversion of Hounsfield units from a computed tomography (CT) image to cons...

Multi-structure bone segmentation in pediatric MR images with combined regularization from shape priors and adversarial network.

Artificial intelligence in medicine
Morphological and diagnostic evaluation of pediatric musculoskeletal system is crucial in clinical practice. However, most segmentation models do not perform well on scarce pediatric imaging data. We propose a new pre-trained regularized convolutiona...