AIMC Topic: Deep Learning

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Attenuation correction and truncation completion for breast PET/MR imaging using deep learning.

Physics in medicine and biology
. Simultaneous PET/MR scanners combine the high sensitivity of MR imaging with the functional imaging of PET. However, attenuation correction of breast PET/MR imaging is technically challenging. The purpose of this study is to establish a robust atte...

Enhanced multimodal biometric recognition systems based on deep learning and traditional methods in smart environments.

PloS one
In the field of data security, biometric security is a significant emerging concern. The multimodal biometrics system with enhanced accuracy and detection rate for smart environments is still a significant challenge. The fusion of an electrocardiogra...

Comparing ARIMA and various deep learning models for long-term water quality index forecasting in Dez River, Iran.

Environmental science and pollution research international
Water scarcity poses a significant global challenge, particularly in developing nations like Iran. Consequently, there is a pressing requirement for ongoing monitoring and prediction of water quality, utilizing advanced techniques characterized by lo...

Training of a deep learning based digital subtraction angiography method using synthetic data.

Medical physics
BACKGROUND: Digital subtraction angiography (DSA) is a fluoroscopy method primarily used for the diagnosis of cardiovascular diseases (CVDs). Deep learning-based DSA (DDSA) is developed to extract DSA-like images directly from fluoroscopic images, wh...

UDRSNet: An unsupervised deformable registration module based on image structure similarity.

Medical physics
BACKGROUND: Image registration is a challenging problem in many clinical tasks, but deep learning has made significant progress in this area over the past few years. Real-time and robust registration has been made possible by supervised transformatio...

A Q-transform-based deep learning model for the classification of atrial fibrillation types.

Physical and engineering sciences in medicine
According to the World Health Organization (WHO), Atrial Fibrillation (AF) is emerging as a global epidemic, which has resulted in a need for techniques to accurately diagnose AF and its various subtypes. While the classification of cardiac arrhythmi...

Nanozyme-induced deep learning-assisted smartphone integrated colorimetric and fluorometric dual-mode for detection of tetracycline analogs.

Analytica chimica acta
In this work, a colorimetric and fluorescent dual-mode probe controlled by NH-MIL-88 B (Fe, Ni) nanozymes was developed to visually detect tetracycline antibiotics (TCs) residues quantitatively, as well as accurately distinguish the four most widely ...

Integration of deep learning and improved multi-objective algorithm to optimize reservoir operation for balancing human and downstream ecological needs.

Water research
Dam (reservoir)-induced alterations of flow and water temperature regimes can threaten downstream fish habitats and native aquatic ecosystems. Alleviating the negative environmental impacts of dam-reservoir and balancing the multiple purposes of rese...

Estimating four-decadal variations of seagrass distribution using satellite data and deep learning methods in a marine lagoon.

The Science of the total environment
Seagrasses are marine flowering plants that inhabit shallow coastal and estuarine waters and serve vital ecological functions in marine ecosystems. However, seagrass ecosystems face the looming threat of degradation, necessitating effective monitorin...

Innovative approach for predicting daily reference evapotranspiration using improved shallow and deep learning models in a coastal region: A comparative study.

Journal of environmental management
Accurate and reliable estimation of Reference Evapotranspiration (ETo) is crucial for water resources management, hydrological processes, and agricultural production. The FAO-56 Penman-Monteith (FAO-56PM) approach is recommended as the standard model...