AIMC Journal:
IEEE transactions on medical imaging

Showing 281 to 290 of 687 articles

A Hybrid Approach for Approximating the Ideal Observer for Joint Signal Detection and Estimation Tasks by Use of Supervised Learning and Markov-Chain Monte Carlo Methods.

IEEE transactions on medical imaging May 2, 2022
The ideal observer (IO) sets an upper performance limit among all observers and has been advocated for assessing and optimizing imaging systems. For general joint detection and estimation (detection-estimation) tasks, estimation ROC (EROC) analysis h...
ROC Curve Monte Carlo Method Markov Chains Supervised Machine Learning Bayes Theorem Computer Simulation
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FractureNet: A 3D Convolutional Neural Network Based on the Architecture of m-Ary Tree for Fracture Type Identification.

IEEE transactions on medical imaging May 2, 2022
To address the problem of automatic identification of fine-grained fracture types, in this paper, we propose a novel framework using 3D convolutional neural network (CNN) to learn fracture features from voxelized bone models which are obtained by est...
Trees Neural Networks, Computer Humans
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Unsupervised Deep Learning for FOD-Based Susceptibility Distortion Correction in Diffusion MRI.

IEEE transactions on medical imaging May 2, 2022
Susceptibility induced distortion is a major artifact that affects the diffusion MRI (dMRI) data analysis. In the Human Connectome Project (HCP), the state-of-the-art method adopted to correct this kind of distortion is to exploit the displacement fi...
Connectome Diffusion Magnetic Resonance Imaging Artifacts Brain Image Processing, Computer-Assisted Deep Learning Humans
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MHA-CoroCapsule: Multi-Head Attention Routing-Based Capsule Network for COVID-19 Chest X-Ray Image Classification.

IEEE transactions on medical imaging May 2, 2022
The outbreak of COVID-19 threatens the lives and property safety of countless people and brings a tremendous pressure to health care systems worldwide. The principal challenge in the fight against this disease is the lack of efficient detection metho...
COVID-19 SARS-CoV-2 Neural Networks, Computer Humans Attention Deep Learning X-Rays
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Deep-Learning-Based Automated Neuron Reconstruction From 3D Microscopy Images Using Synthetic Training Images.

IEEE transactions on medical imaging May 2, 2022
Digital reconstruction of neuronal structures from 3D microscopy images is critical for the quantitative investigation of brain circuits and functions. It is a challenging task that would greatly benefit from automatic neuron reconstruction methods. ...
Neurons Microscopy Image Processing, Computer-Assisted Algorithms Imaging, Three-Dimensional Deep Learning
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Domain Adaptation Meets Zero-Shot Learning: An Annotation-Efficient Approach to Multi-Modality Medical Image Segmentation.

IEEE transactions on medical imaging May 2, 2022
Due to the lack of properly annotated medical data, exploring the generalization capability of the deep model is becoming a public concern. Zero-shot learning (ZSL) has emerged in recent years to equip the deep model with the ability to recognize uns...
Heart Databases, Genetic Semantics Machine Learning
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KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentation.

IEEE transactions on medical imaging Apr 1, 2022
Most methods for medical image segmentation use U-Net or its variants as they have been successful in most of the applications. After a detailed analysis of these "traditional" encoder-decoder based approaches, we observed that they perform poorly in...
Neural Networks, Computer Image Processing, Computer-Assisted
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Multi-Task Fusion for Improving Mammography Screening Data Classification.

IEEE transactions on medical imaging Apr 1, 2022
Machine learning and deep learning methods have become essential for computer-assisted prediction in medicine, with a growing number of applications also in the field of mammography. Typically these algorithms are trained for a specific task, e.g., t...
Breast Neoplasms Neural Networks, Computer Early Detection of Cancer Female Algorithms Mammography Machine Learning Humans
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Two-Stream Graph Convolutional Network for Intra-Oral Scanner Image Segmentation.

IEEE transactions on medical imaging Apr 1, 2022
Precise segmentation of teeth from intra-oral scanner images is an essential task in computer-aided orthodontic surgical planning. The state-of-the-art deep learning-based methods often simply concatenate the raw geometric attributes (i.e., coordinat...
Tooth Humans Image Processing, Computer-Assisted Neural Networks, Computer
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Explanation and Use of Uncertainty Quantified by Bayesian Neural Network Classifiers for Breast Histopathology Images.

IEEE transactions on medical imaging Apr 1, 2022
Despite the promise of Convolutional neural network (CNN) based classification models for histopathological images, it is infeasible to quantify its uncertainties. Moreover, CNNs may suffer from overfitting when the data is biased. We show that Bayes...
Bayes Theorem Uncertainty Breast Neural Networks, Computer
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