AIMC Topic: Deep Learning

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Comparison of machine learning and deep learning models for evaluating suitable areas for premium teas in Yunnan, China.

PloS one
BACKGROUND: Tea is an important economic crop in Yunnan, and the market price of premium teas such as Lao Banzhang is significantly higher than ordinary teas. For planting lands to promote, the tea industry to develop and minority lands' economies to...

Super-resolution 4D flow MRI to quantify aortic regurgitation using computational fluid dynamics and deep learning.

The international journal of cardiovascular imaging
Changes in cardiovascular hemodynamics are closely related to the development of aortic regurgitation (AR), a type of valvular heart disease. Metrics derived from blood flows are used to indicate AR onset and evaluate its severity. These metrics can ...

Evaluation of the area subscore of the Palmoplantar Pustulosis Area and Severity Index using an attention U-net deep learning algorithm.

The Journal of dermatology
Palmoplantar pustulosis (PPP) is a variant of pustular psoriasis involving the palms and soles. The severity of PPP is usually evaluated using the Palmoplantar Pustulosis Area and Severity Index (PPPASI). Among the components of the PPPASI, the area ...

TSMC-Net: Deep-Learning Multigas Classification Using THz Absorption Spectra.

ACS sensors
The identification of gas mixture speciation from a complex multicomponent absorption spectrum is a problem in gas sensing that can be addressed using machine-learning approaches. Here, we report on a deep convolutional neural network for multigas cl...

Field-dependent deep learning enables high-throughput whole-cell 3D super-resolution imaging.

Nature methods
Single-molecule localization microscopy in a typical wide-field setup has been widely used for investigating subcellular structures with super resolution; however, field-dependent aberrations restrict the field of view (FOV) to only tens of micromete...

A Deep Learning Image System for Classifying High Oleic Sunflower Seed Varieties.

Sensors (Basel, Switzerland)
Sunflower seeds, one of the main oilseeds produced around the world, are widely used in the food industry. Mixtures of seed varieties can occur throughout the supply chain. Intermediaries and the food industry need to identify the varieties to produc...

Deep learning based unpaired image-to-image translation applications for medical physics: a systematic review.

Physics in medicine and biology
. There is a growing number of publications on the application of unpaired image-to-image (I2I) translation in medical imaging. However, a systematic review covering the current state of this topic for medical physicists is lacking. The aim of this a...

Evaluation of auto-segmentation for brachytherapy of postoperative cervical cancer using deep learning-based workflow.

Physics in medicine and biology
. The purpose of this study was to evaluate the accuracy of brachytherapy (BT) planning structures derived from Deep learning (DL) based auto-segmentation compared with standard manual delineation for postoperative cervical cancer.. We introduced a c...

Deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for predicted tumor probability in FDG PET and CT images.

Physics in medicine and biology
 Tumor segmentation is a fundamental step for radiotherapy treatment planning. To define an accurate segmentation of the primary tumor (GTVp) of oropharyngeal cancer patients (OPC) each image volume is explored slice-by-slice from different orientati...

Deep learning for the diagnosis of mesial temporal lobe epilepsy.

PloS one
OBJECTIVE: This study aimed to enable the automatic detection of the hippocampus and diagnose mesial temporal lobe epilepsy (MTLE) with the hippocampus as the epileptogenic area using artificial intelligence (AI). We compared the diagnostic accuracie...