AIMC Topic: Image Processing, Computer-Assisted

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Generative Neural Framework for Micro-Vessels Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The morphological abnormalities in the retinal blood vessel have a close association with cerebrovascular, cardio-vascular, and systemic diseases. It makes the retinal artery/vein (A/V) classification salient for clinical decision-making. The existin...

Grade classification of nasal obstruction from endoscopy videos using machine learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nasal obstruction (NO), referring to blockage in the nasal cavity, is prevalent, affecting approximately one-third of the adult population. Consequently, diagnosis typically requires a combination of medical imaging techniques and tests, as NO is oft...

EDRAM-Net: Encoder-Decoder with Residual Attention Module Network for Low-dose Computed Tomography Reconstruction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The medical application of Computed Tomography (CT) is to provide detailed anatomical structures of patients without the need for invasive procedures like surgery, which is very useful for clinicians in disease diagnosis. Excessive radiation exposure...

Single Bone Modeler: deep learning bone segmentation for cone-beam CT.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The accurate segmentation and modeling of bones play a crucial role in diagnosis and surgical planning in orthopedics. Traditional methods face challenges in capturing the fine details and complex structures present in cone-beam computed tomography (...

Dual Prototypical Self-Supervised Learning for One-shot Medical Image Segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Medical image segmentation using deep learning typically requires a large quantity of well-annotated data. However, the acquisition of pixel-level annotations is arduous and expensive, often requiring the expertise of experienced medical professional...

Ultrasound for Automated Classification of Full-Thickness Rotator Cuff Tendon Tears using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Rotator cuff tendon tears, the most common shoulder injuries, are typically diagnosed mainly through MRI, but can also be seen on ultrasound (US), a much less costly test that currently requires highly-trained human expert operators. An AI tool to id...

COINS: Counting Cones Using Inpainting Based Self-supervised Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
A novel approach for "COunting cones using IN-painting based Self-supervised learning (SSL)"(COINS), in wide field-of-view, low-resolution Adaptive Optics (AO) images is described. The proposed approach is applied to a dataset of 4°×4° AO images capt...

Hard example mining in Multi-Instance Learning for Whole-Slide Image Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Multiple instance learning(MIL) has shown superior performance in the classification of whole-slide images(WSIs). The implementation of multiple instance learning for WSI classification typically involves two components, i.e., a feature extractor, wh...

CBCRnet: A Contrastive Learning-based Multi-modal Image Registration Via Bidirectional Cross-modal Attention.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In the past few years, convolutional neural networks (CNNs) have been a major focus in medical image registration. However, it has been proved that CNNs are limited in their ability to represent modal-independent feature and understand the spatial co...

Dual Attention Graph Convolutional Network Fusing Imaging and Genetic Data for Early Alzheimer's Disease Diagnosis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Alzheimer's Disease (AD) poses a significant global neurodegenerative challenge, underscoring the urgency of early clinical intervention. Our paper presents a novel approach for early AD diagnosis, focusing on a dual attention graph convolutional net...