AIMC Topic: Deep Learning

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Synthetic Data for Multi-Parameter Camera-Based Physiological Sensing.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Synthetic data is a powerful tool in training data hungry deep learning algorithms. However, to date, camera-based physiological sensing has not taken full advantage of these techniques. In this work, we leverage a high-fidelity synthetics pipeline f...

An Efficient Deep Learning Network for Automatic Detection of Neovascularization in Color Fundus Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Retinopathy screening is a non-invasive method to collect retinal images and neovascularization detection from retinal images plays a significant role on the identification and classification of diabetes retinopathy. In this paper, an efficient deep ...

DeepQSMSeg: A Deep Learning-based Sub-cortical Nucleus Segmentation Tool for Quantitative Susceptibility Mapping.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Deep brain nuclei are closely related to the pathogenesis of neurodegenerative diseases. Automatic segmentation for brain nuclei plays a significant role in aging and disease-related assessment. Quantitative susceptibility mapping (QSM), as a novel M...

Deep-ReAP: Deep Representations And Partial label learning for Multi-pathology Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automated detection of pathology in images with multiple pathologies is one of the most challenging problems in medical diagnostics. The primary hurdles for automated systems include data imbalance across pathology categories and structural variation...

Forward Model and Deep Learning Based Iterative Deconvolution for Robust Dynamic CT Perfusion.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Perfusion maps obtained from low-dose computed tomography (CT) data suffer from poor signal to noise ratio. To enhance the quality of the perfusion maps, several works rely on denoising the low-dose CT (LD-CT) images followed by conventional regulari...

A Novel Adaptive Fuzzy Deep Learning Approach for Histopathologic Cancer Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We proposed a novel model that integrates the fuzzy theory and group equivariant convolutional neural network for histopathologic cancer detection. The proposed fuzzy group equivariant convolutional neural network consists of the convolutional networ...

Multi-modal Broad Learning System for Medical Image and Text-based Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic classification of medical images plays an essential role in computer-aided diagnosis. However, the medical images arise from the small number of available data and the improvement of existing data-enhancement methods are limited. In order t...

Deep learning model for automatic prostate segmentation on bicentric T2w images with and without endorectal coil.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic segmentation of the prostate on Magnetic Resonance Imaging (MRI) is one of the topics on which research has focused in recent years as it is a fundamental first step in the building process of a Computer aided diagnosis (CAD) system for can...

Deep Learning for Predicting Gamma-Ray Interaction Positions in LYSO Detector.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Positron Emission Tomography (PET) is among the most commonly used medical imaging modalities in clinical practice, especially for oncological applications. In contrast to conventional imaging modalities like X-ray Computed Tomography (CT) or Magneti...

Seizure Type Classification Using EEG Based on Gramian Angular Field Transformation and Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
classification of seizure types plays a crucial role in diagnosis and prognosis of epileptic patients which has not been addressed properly, while most of the works are surrounded by seizure detection only. However, in recent times, few works have be...