AIMC Topic: Deep Learning

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Solving visual pollution with deep learning: A new nexus in environmental management.

Journal of environmental management
Visual pollution is a relatively new concern amidst the existing plethora of mainstream environmental pollution, recommending the necessity for research to conceptualize, formalize, quantify and assess it from different dimensions. The purpose of thi...

Cine MRI analysis by deep learning of optical flow: Adding the temporal dimension.

Computers in biology and medicine
Accurate segmentation of the left ventricle (LV) from cine magnetic resonance imaging (MRI) is an important step in the reliable assessment of cardiac function in cardiovascular disease patients. Several deep learning convolutional neural network (CN...

Robust contour propagation using deep learning and image registration for online adaptive proton therapy of prostate cancer.

Medical physics
PURPOSE: To develop and validate a robust and accurate registration pipeline for automatic contour propagation for online adaptive Intensity-Modulated Proton Therapy (IMPT) of prostate cancer using elastix software and deep learning.

Deep PPG: Large-Scale Heart Rate Estimation with Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Photoplethysmography (PPG)-based continuous heart rate monitoring is essential in a number of domains, e.g., for healthcare or fitness applications. Recently, methods based on time-frequency spectra emerged to address the challenges of motion artefac...

Cross-Cell-Type Prediction of TF-Binding Site by Integrating Convolutional Neural Network and Adversarial Network.

International journal of molecular sciences
Transcription factor binding sites (TFBSs) play an important role in gene expression regulation. Many computational methods for TFBS prediction need sufficient labeled data. However, many transcription factors (TFs) lack labeled data in cell types. W...

Incorporating imaging information from deep neural network layers into image guided radiation therapy (IGRT).

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: To investigate a novel markerless prostate localization strategy using a pre-trained deep learning model to interpret routine projection kilovoltage (kV) X-ray images in image-guided radiation therapy (IGRT).

Using a deep learning system in endoscopy for screening of early esophageal squamous cell carcinoma (with video).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Few artificial intelligence-based technologies have been developed to improve the efficiency of screening for esophageal squamous cell carcinoma (ESCC). Here, we developed and validated a novel system of computer-aided detection ...

Automatic detection and diagnosis of sacroiliitis in CT scans as incidental findings.

Medical image analysis
Early diagnosis of sacroiliitis may lead to preventive treatment which can significantly improve the patient's quality of life in the long run. Oftentimes, a CT scan of the lower back or abdomen is acquired for suspected back pain. However, since the...

Deep learning derived tumor infiltration maps for personalized target definition in Glioblastoma radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: Glioblastoma is routinely treated by concomitant radiochemotherapy. Current target definition guidelines use anatomic MRI (magnetic resonance imaging) scans, taking into account contrast enhancement and the rather unspecific hyperintensity o...

Machine and deep learning meet genome-scale metabolic modeling.

PLoS computational biology
Omic data analysis is steadily growing as a driver of basic and applied molecular biology research. Core to the interpretation of complex and heterogeneous biological phenotypes are computational approaches in the fields of statistics and machine lea...