AIMC Topic: Deep Learning

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Deep learning-based assessment of body composition and liver tumour burden for survival modelling in advanced colorectal cancer.

Journal of cachexia, sarcopenia and muscle
BACKGROUND: Personalized therapy planning remains a significant challenge in advanced colorectal cancer care, despite extensive research on prognostic and predictive markers. A strong correlation of sarcopenia or overall body composition and survival...

Deep learning-based system for automatic prediction of triple-negative breast cancer from ultrasound images.

Medical & biological engineering & computing
To develop a deep-learning system for the automatic identification of triple-negative breast cancer (TNBC) solely from ultrasound images. A total of 145 patients and 831 images were retrospectively enrolled at Peking Union College Hospital from April...

Virus Detection and Identification in Minutes Using Single-Particle Imaging and Deep Learning.

ACS nano
The increasing frequency and magnitude of viral outbreaks in recent decades, epitomized by the COVID-19 pandemic, has resulted in an urgent need for rapid and sensitive diagnostic methods. Here, we present a methodology for virus detection and identi...

Deep Learning in Diverse Intelligent Sensor Based Systems.

Sensors (Basel, Switzerland)
Deep learning has become a predominant method for solving data analysis problems in virtually all fields of science and engineering. The increasing complexity and the large volume of data collected by diverse sensor systems have spurred the developme...

Intelligent Reflecting Surface-Assisted Physical Layer Key Generation with Deep Learning in MIMO Systems.

Sensors (Basel, Switzerland)
Physical layer secret key generation (PLKG) is a promising technology for establishing effective secret keys. Current works for PLKG mostly study key generation schemes in ideal communication environments with little or even no signal interference. I...

Dicentric chromosome assay using a deep learning-based automated system.

Scientific reports
The dicentric chromosome assay is the "gold standard" in biodosimetry for estimating radiation exposure. However, its large-scale deployment is limited owing to its time-consuming nature and requirement for expert reviewers. Therefore, a recently dev...

A clinical and time savings evaluation of a deep learning automatic contouring algorithm.

Medical dosimetry : official journal of the American Association of Medical Dosimetrists
Automatic contouring algorithms may streamline clinical workflows by reducing normal organ-at-risk (OAR) contouring time. Here we report the first comprehensive quantitative and qualitative evaluation, along with time savings assessment for a prototy...

A deep learning method for predicting lead content in oilseed rape leaves using fluorescence hyperspectral imaging.

Food chemistry
The purpose of this study was to develop a deep learning method involving wavelet transform (WT) and stacked denoising autoencoder (SDAE) for extracting deep features of heavy metal lead (Pb) detection of oilseed rape leaves. Firstly, the standard no...

Laser ultrasonic imaging of complex defects with full-matrix capture and deep-learning extraction.

Ultrasonics
Phased array-based full-matrix ultrasonic imaging has been the golden standard for the non-destructive evaluation of critical components. However, the piezoelectric phased array cannot be applied in hazardous environments and online monitoring due to...