AIMC Topic: Deep Learning

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Integrating spatial gene expression and breast tumour morphology via deep learning.

Nature biomedical engineering
Spatial transcriptomics allows for the measurement of RNA abundance at a high spatial resolution, making it possible to systematically link the morphology of cellular neighbourhoods and spatially localized gene expression. Here, we report the develop...

Dense anatomical annotation of slit-lamp images improves the performance of deep learning for the diagnosis of ophthalmic disorders.

Nature biomedical engineering
The development of artificial intelligence algorithms typically demands abundant high-quality data. In medicine, the datasets that are required to train the algorithms are often collected for a single task, such as image-level classification. Here, w...

Automatic segmentation of pelvic organs-at-risk using a fusion network model based on limited training samples.

Acta oncologica (Stockholm, Sweden)
Efficient and accurate methods are needed to automatically segmenting organs-at-risk (OAR) to accelerate the radiotherapy workflow and decrease the treatment wait time. We developed and evaluated the use of a fused model Dense V-Network for its abil...

Superpixel-based deep convolutional neural networks and active contour model for automatic prostate segmentation on 3D MRI scans.

Medical & biological engineering & computing
Automatic and reliable prostate segmentation is an essential prerequisite for assisting the diagnosis and treatment, such as guiding biopsy procedure and radiation therapy. Nonetheless, automatic segmentation is challenging due to the lack of clear p...

Deep learning-based pulmonary nodule detection: Effect of slab thickness in maximum intensity projections at the nodule candidate detection stage.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: To investigate the effect of the slab thickness in maximum intensity projections (MIPs) on the candidate detection performance of a deep learning-based computer-aided detection (DL-CAD) system for pulmonary nodule detection ...

Explainable Deep Learning for Pulmonary Disease and Coronavirus COVID-19 Detection from X-rays.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Coronavirus disease (COVID-19) is an infectious disease caused by a new virus never identified before in humans. This virus causes respiratory disease (for instance, flu) with symptoms such as cough, fever and, in severe cas...

Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis.

Medical image analysis
Supervised training of deep learning models requires large labeled datasets. There is a growing interest in obtaining such datasets for medical image analysis applications. However, the impact of label noise has not received sufficient attention. Rec...

Age-related Macular Degeneration: Nutrition, Genes and Deep Learning-The LXXVI Edward Jackson Memorial Lecture.

American journal of ophthalmology
PURPOSE: To evaluate the importance of nutritional supplements, dietary pattern, and genetic associations in age-related macular degeneration (AMD); and to discuss the technique of artificial intelligence/deep learning to potentially enhance research...

Task-based characterization of a deep learning image reconstruction and comparison with filtered back-projection and a partial model-based iterative reconstruction in abdominal CT: A phantom study.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: We aimed to thoroughly characterize image quality of a novel deep learning image reconstruction (DLIR), and investigate its potential for dose reduction in abdominal CT in comparison with filtered back-projection (FBP) and a partial model-ba...

Boosting radiotherapy dose calculation accuracy with deep learning.

Journal of applied clinical medical physics
In radiotherapy, a trade-off exists between computational workload/speed and dose calculation accuracy. Calculation methods like pencil-beam convolution can be much faster than Monte-Carlo methods, but less accurate. The dose difference, mostly cause...