AIMC Topic: Deep Learning

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A fully automated hybrid human sperm detection and classification system based on mobile-net and the performance comparison with conventional methods.

Medical & biological engineering & computing
Sperm morphology, as an indicator of fertility, is a critical tool in semen analysis. In this study, a smartphone-based hybrid system that fully automates the sperm morphological analysis is introduced with the aim of eliminating unwanted human facto...

Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer.

Nature communications
Accurate identification of axillary lymph node (ALN) involvement in patients with early-stage breast cancer is important for determining appropriate axillary treatment options and therefore avoiding unnecessary axillary surgery and complications. Her...

Deep learning-based target metabolite isolation and big data-driven measurement uncertainty estimation in proton magnetic resonance spectroscopy of the brain.

Magnetic resonance in medicine
PURPOSE: The aim of this study was to develop a method for metabolite quantification with simultaneous measurement uncertainty estimation in deep learning-based proton magnetic resonance spectroscopy ( H-MRS).

Adaptive and Compressive Beamforming Using Deep Learning for Medical Ultrasound.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
In ultrasound (US) imaging, various types of adaptive beamforming techniques have been investigated to improve the resolution and the contrast-to-noise ratio of the delay and sum (DAS) beamformers. Unfortunately, the performance of these adaptive bea...

An integrated deep learning framework for joint segmentation of blood pool and myocardium.

Medical image analysis
Simultaneous and automatic segmentation of the blood pool and myocardium is an important precondition for early diagnosis and pre-operative planning in patients with complex congenital heart disease. However, due to the high diversity of cardiovascul...

Hierarchical Organization of Functional Brain Networks Revealed by Hybrid Spatiotemporal Deep Learning.

Brain connectivity
Hierarchical organization of brain function has been an established concept in the neuroscience field for a long time, however, it has been rarely demonstrated how such hierarchical macroscale functional networks are actually organized in the human b...

Exploring the effect of hypertension on retinal microvasculature using deep learning on East Asian population.

PloS one
Hypertension is the leading risk factor of cardiovascular disease and has profound effects on both the structure and function of the microvasculature. Abnormalities of the retinal vasculature may reflect the degree of microvascular damage due to hype...

Deep learning approach to classification of lung cytological images: Two-step training using actual and synthesized images by progressive growing of generative adversarial networks.

PloS one
Cytology is the first pathological examination performed in the diagnosis of lung cancer. In our previous study, we introduced a deep convolutional neural network (DCNN) to automatically classify cytological images as images with benign or malignant ...

NFN+: A novel network followed network for retinal vessel segmentation.

Neural networks : the official journal of the International Neural Network Society
In the early diagnosis of diabetic retinopathy, the morphological attributes of blood vessels play an essential role to construct a retinal computer-aided diagnosis system. However, due to the challenges including limited densely annotated data, inte...

Interpretable Artificial Intelligence: Why and When.

AJR. American journal of roentgenology
The purpose of this article is to discuss the problem of interpretability of artificial intelligence (AI) and highlight the need for continuing scientific discovery using AI algorithms to deal with medical big data. A plethora of AI algorithms are ...