AIMC Topic: Image Processing, Computer-Assisted

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Fully Automatic Arteriovenous Segmentation in Retinal Images via Topology-Aware Generative Adversarial Networks.

Interdisciplinary sciences, computational life sciences
Retinal image contains rich information on the blood vessel and is highly related to vascular diseases. Fully automatic and accurate identification of arteries and veins from the complex background of retinal images is essential for analyzing eye-rel...

Deep learning-based image analysis methods for brightfield-acquired multiplex immunohistochemistry images.

Diagnostic pathology
BACKGROUND: Multiplex immunohistochemistry (mIHC) permits the labeling of six or more distinct cell types within a single histologic tissue section. The classification of each cell type requires detection of the unique colored chromogens localized to...

Cone-beam CT-derived relative stopping power map generation via deep learning for proton radiotherapy.

Medical physics
PURPOSE: In intensity-modulated proton therapy (IMPT), protons are used to deliver highly conformal dose distributions, targeting tumors, and sparing organs-at-risk. However, due to uncertainties in both patient setup and relative stopping power (RSP...

Automatic characterization of myocardial perfusion imaging polar maps employing deep learning and data augmentation.

Hellenic journal of nuclear medicine
OBJECTIVE: To investigate a deep learning technique, more specifically state-of-the-art convolutional neural networks (CNN), for automatic characterization of polar maps derived from myocardial perfusion imaging (MPI) studies for the diagnosis of cor...

An automated detection system for colonoscopy images using a dual encoder-decoder model.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Conventional computer-aided detection systems (CADs) for colonoscopic images utilize shape, texture, or temporal information to detect polyps, so they have limited sensitivity and specificity. This study proposes a method to extract possible polyp fe...

Unsupervised multi-domain multimodal image-to-image translation with explicit domain-constrained disentanglement.

Neural networks : the official journal of the International Neural Network Society
Image-to-image translation has drawn great attention during the past few years. It aims to translate an image in one domain to a target image in another domain. However, three big challenges remain in image-to-image translation: (1) the lack of large...

A deep learning system to obtain the optimal parameters for a threshold-based breast and dense tissue segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Breast cancer is the most frequent cancer in women. The Spanish healthcare network established population-based screening programs in all Autonomous Communities, where mammograms of asymptomatic women are taken with early di...

The effect of deep convolutional neural networks on radiologists' performance in the detection of hip fractures on digital pelvic radiographs.

European journal of radiology
PURPOSE: The purpose of our study is to develop deep convolutional neural network (DCNN) for detecting hip fractures using CT and MRI as a gold standard, and to evaluate the diagnostic performance of 7 readers with and without DCNN.

Using an ontology of the human cardiovascular system to improve the classification of histological images.

Scientific reports
The advantages of automatically recognition of fundamental tissues using computer vision techniques are well known, but one of its main limitations is that sometimes it is not possible to classify correctly an image because the visual information is ...

Label-Free Quantification of Pharmacokinetics in Skin with Stimulated Raman Scattering Microscopy and Deep Learning.

The Journal of investigative dermatology
The treatment of inflammatory skin conditions relies on a deep understanding of how drugs and tissue behave and interact. Although numerous methods have been developed that aim to follow and quantify topical drug pharmacokinetics, these tools can com...