AIMC Topic: Neural Networks, Computer

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Deformable US/CT Image Registration with a Convolutional Neural Network for Cardiac Arrhythmia Therapy.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Image registration represents one of the fundamental techniques in medical imaging and image-guided interventions. In this paper, we present a Convolutional Neural Network (CNN) framework for deformable transesophageal US/CT image registration, for t...

Prediction of Patient Demographics using 3D Craniofacial Scans and Multi-view CNNs.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
3D data is becoming increasingly popular and accessible for computer vision tasks. A popular format for 3D data is the mesh format, which can depict a 3D surface accurately and cost-effectively by connecting points in the (x, y, z) plane, known as ve...

Deep Learning in ex-vivo Lung Cancer Discrimination using Fluorescence Lifetime Endomicroscopic Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Fluorescence lifetime is effective in discriminating cancerous tissue from normal tissue, but conventional discrimination methods are primarily based on statistical approaches in collaboration with prior knowledge. This paper investigates the applica...

OrgaNet: A Robust Network for Subcellular Organelles Classification in Fluorescence Microscopy Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic identification of subcellular compartments of proteins in fluorescence microscopy images is an important task to quantitatively evaluate cellular processes. A common problem for the development of deep learning based classifiers is that the...

Super-resolution technology to simultaneously improve optical & digital resolution of optical coherence tomography via deep learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Optical coherence tomography (OCT) has stimulated a wide range of medical image-based diagnosis and treatment. In cardiac imaging, OCT has been used in assessing plaques before and after stenting. While needed in many scenarios, high resolution comes...

Prediction for Morphology and States of Stem Cell Colonies using a LSTM Network with Progressive Training Microscopy Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We present a new LSTM (P-LSTM: Progressive LSTM) network, aiming to predict morphology and states of cell colonies from time-lapse microscopy images. Apparent short-term changes occur in some types of time-lapse cell images. Therefore, long-term-memo...

Training Deep Neural Networks for Small and Highly Heterogeneous MRI Datasets for Cancer Grading.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Using medical images recorded in clinical practice has the potential to be a game-changer in the application of machine learning for medical decision support. Thousands of medical images are produced in daily clinical activity. The diagnosis of medic...

Efficient Deep Learning-based Wound-bed Segmentation For Mobile Applications.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper proposes a deep learning image segmentation method for the purpose of segmenting wound-bed regions from the background. Our contributions include proposing a fast and efficient convolutional neural networks (CNN)-based segmentation network...

Extracting Membrane Borders in IVUS Images Using a Multi-Scale Feature Aggregated U-Net.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic extraction of the lumen-intima border (LIB) and the media-adventitia border (MAB) in intravascular ultrasound (IVUS) images is of high clinical interest. Despite the superior performance achieved by deep neural networks (DNNs) on various me...

UENet: A Novel Generative Adversarial Network for Angiography Image Segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Convolutional neural networks (CNNs) have been widely used in medical image segmentation. Vessel segmentation in coronary angiography remains a challenging task. It is a great challenge to extract fine features of coronary artery for segmentation due...