AIMC Topic: Image Processing, Computer-Assisted

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Hyper-reflective foci segmentation in SD-OCT retinal images with diabetic retinopathy using deep convolutional neural networks.

Medical physics
PURPOSE: The purpose of this study was to automatically and accurately segment hyper-reflective foci (HRF) in spectral domain optical coherence tomography (SD-OCT) images with diabetic retinopathy (DR) using deep convolutional neural networks.

Functional connectivity-based classification of autism and control using SVM-RFECV on rs-fMRI data.

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)
Considering the unsatisfactory classification accuracy of autism due to unsuitable features selected in current studies, a functional connectivity (FC)-based algorithm for classifying autism and control using support vector machine-recursive feature ...

A non-linear mathematical model using optical sensor to predict heart decellularization efficacy.

Scientific reports
One of the main problems of the decellularization technique is the subjectivity of the final evaluation of its efficacy in individual organs. This problem can result in restricted cell repopulation reproducibility and worse responses to transplant ti...

An investigation of quantitative accuracy for deep learning based denoising in oncological PET.

Physics in medicine and biology
Reducing radiation dose is important for PET imaging. However, reducing injection doses causes increased image noise and low signal-to-noise ratio (SNR), subsequently affecting diagnostic and quantitative accuracies. Deep learning methods have shown ...

Deep Learning Diffuse Optical Tomography.

IEEE transactions on medical imaging
Diffuse optical tomography (DOT) has been investigated as an alternative imaging modality for breast cancer detection thanks to its excellent contrast to hemoglobin oxidization level. However, due to the complicated non-linear photon scattering physi...

EmoCo: Visual Analysis of Emotion Coherence in Presentation Videos.

IEEE transactions on visualization and computer graphics
Emotions play a key role in human communication and public presentations. Human emotions are usually expressed through multiple modalities. Therefore, exploring multimodal emotions and their coherence is of great value for understanding emotional exp...

Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets.

Medical physics
PURPOSE: Accurate tumor segmentation is a requirement for magnetic resonance (MR)-based radiotherapy. Lack of large expert annotated MR datasets makes training deep learning models difficult. Therefore, a cross-modality (MR-CT) deep learning segmenta...

Precise estimation of renal vascular dominant regions using spatially aware fully convolutional networks, tensor-cut and Voronoi diagrams.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This paper presents a new approach for precisely estimating the renal vascular dominant region using a Voronoi diagram. To provide computer-assisted diagnostics for the pre-surgical simulation of partial nephrectomy surgery, we must obtain informatio...

Convolution kernel and iterative reconstruction affect the diagnostic performance of radiomics and deep learning in lung adenocarcinoma pathological subtypes.

Thoracic cancer
BACKGROUND: The aim of this study was to investigate the influence of convolution kernel and iterative reconstruction on the diagnostic performance of radiomics and deep learning (DL) in lung adenocarcinomas.

Multi-representation adaptation network for cross-domain image classification.

Neural networks : the official journal of the International Neural Network Society
In image classification, it is often expensive and time-consuming to acquire sufficient labels. To solve this problem, domain adaptation often provides an attractive option given a large amount of labeled data from a similar nature but different doma...