AIMC Topic: Image Processing, Computer-Assisted

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Bioimage-Based Prediction of Protein Subcellular Location in Human Tissue with Ensemble Features and Deep Networks.

IEEE/ACM transactions on computational biology and bioinformatics
Prediction of protein subcellular location has currently become a hot topic because it has been proven to be useful for understanding both the disease mechanisms and novel drug design. With the rapid development of automated microscopic imaging techn...

nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation.

Nature methods
Biomedical imaging is a driver of scientific discovery and a core component of medical care and is being stimulated by the field of deep learning. While semantic segmentation algorithms enable image analysis and quantification in many applications, t...

MAD-UNet: A deep U-shaped network combined with an attention mechanism for pancreas segmentation in CT images.

Medical physics
PURPOSE: Pancreas segmentation is a difficult task because of the high intrapatient variability in the shape, size, and location of the organ, as well as the low contrast and small footprint of the CT scan. At present, the U-Net model is likely to le...

Deep learning to diagnose cardiac amyloidosis from cardiovascular magnetic resonance.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Cardiovascular magnetic resonance (CMR) is part of the diagnostic work-up for cardiac amyloidosis (CA). Deep learning (DL) is an application of artificial intelligence that may allow to automatically analyze CMR findings and establish the...

An Intelligent Model for the Detection of White Blood Cells using Artificial Intelligence.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The automatic detection and counting of white blood cells (WBCs) play a vital role in the diagnosis of hematological diseases. Computer-aided methods are prevalent in the detection of WBCs because the manual process involves...

Comparison of the suitability of CBCT- and MR-based synthetic CTs for daily adaptive proton therapy in head and neck patients.

Physics in medicine and biology
Cone-beam computed tomography (CBCT)- and magnetic resonance (MR)-images allow a daily observation of patient anatomy but are not directly suited for accurate proton dose calculations. This can be overcome by creating synthetic CTs (sCT) using deep c...

Dictionary learning based image-domain material decomposition for spectral CT.

Physics in medicine and biology
The potential huge advantage of spectral computed tomography (CT) is that it can provide accurate material identification and quantitative tissue information by material decomposition. However, material decomposition is a typical inverse problem, whe...

Coronary angiography image segmentation based on PSPNet.

Computer methods and programs in biomedicine
PURPOSE: Coronary artery disease (CAD) is known to have high prevalence, high disability and mortality. The incidence and mortality of cardiovascular disease are also gradually increasing worldwide. Therefore, our paper proposes to use a more efficie...

PWD-3DNet: A Deep Learning-Based Fully-Automated Segmentation of Multiple Structures on Temporal Bone CT Scans.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The temporal bone is a part of the lateral skull surface that contains organs responsible for hearing and balance. Mastering surgery of the temporal bone is challenging because of this complex and microscopic three-dimensional anatomy. Segmentation o...