AIMC Topic: Deep Learning

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Tackling the Radiological Society of North America Pneumonia Detection Challenge.

AJR. American journal of roentgenology
We provide overviews of deep learning approaches used by two top-placing teams for the 2018 Radiological Society of North America (RSNA) Pneumonia Detection Challenge. Practical applications of deep learning techniques, as well as insights into the...

Pathologist-level classification of histopathological melanoma images with deep neural networks.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: The diagnosis of most cancers is made by a board-certified pathologist based on a tissue biopsy under the microscope. Recent research reveals a high discordance between individual pathologists. For melanoma, the literature reports 25-26% ...

Effect of Depth and Width on Local Minima in Deep Learning.

Neural computation
In this paper, we analyze the effects of depth and width on the quality of local minima, without strong overparameterization and simplification assumptions in the literature. Without any simplification assumption, for deep nonlinear neural networks w...

Multi-Path Dilated Residual Network for Nuclei Segmentation and Detection.

Cells
As a typical biomedical detection task, nuclei detection has been widely used in human health management, disease diagnosis and other fields. However, the task of cell detection in microscopic images is still challenging because the nuclei are common...

Higher SNR PET image prediction using a deep learning model and MRI image.

Physics in medicine and biology
PET images often suffer poor signal-to-noise ratio (SNR). Our objective is to improve the SNR of PET images using a deep neural network (DNN) model and MRI images without requiring any higher SNR PET images in training. Our proposed DNN model consist...

Deep residual network for off-resonance artifact correction with application to pediatric body MRA with 3D cones.

Magnetic resonance in medicine
PURPOSE: To enable rapid imaging with a scan time-efficient 3D cones trajectory with a deep-learning off-resonance artifact correction technique.

Interpretable deep learning to map diagnostic texts to ICD-10 codes.

International journal of medical informatics
BACKGROUND: Automatic extraction of morbid disease or conditions contained in Death Certificates is a critical process, useful for billing, epidemiological studies and comparison across countries. The fact that these clinical documents are written in...

Preliminary study on the application of deep learning system to diagnosis of Sjögren's syndrome on CT images.

Dento maxillo facial radiology
OBJECTIVES: This study estimated the diagnostic performance of a deep learning system for detection of Sjögren's syndrome (SjS) on CT, and compared it with the performance of radiologists.

Automated OCT angiography image quality assessment using a deep learning algorithm.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To expedite and to standardize the process of image quality assessment in optical coherence tomography angiography (OCTA) using a specialized deep learning algorithm (DLA).

Deep Learning to Therapeutically Target Unreported Complexes.

Trends in pharmacological sciences
The disruption of large protein-protein (PP) interfaces remains a challenge in targeted therapy. Designing drugs that compete with binding partners is daunting, especially when the structure of the protein complex is unknown. To address the problem w...