AIMC Topic: Image Processing, Computer-Assisted

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A convolutional neural network Cascade for plantar pressure images registration.

Gait & posture
BACKGROUND: Plantar pressure image (PPI) recorded in high spatial and temporal resolution is very useful in clinical gait analysis. For functional analysis of PPI, image registration is often performed to maximally correlate source image with a templ...

An IoT Based Predictive Modelling for Predicting Lung Cancer Using Fuzzy Cluster Based Segmentation and Classification.

Journal of medical systems
In this paper, we propose a new Internet of Things (IoT) based predictive modelling by using fuzzy cluster based augmentation and classification for predicting the lung cancer disease through continuous monitoring and also to improve the healthcare b...

MR Image Reconstruction Using Deep Density Priors.

IEEE transactions on medical imaging
Algorithms for magnetic resonance (MR) image reconstruction from undersampled measurements exploit prior information to compensate for missing k-space data. Deep learning (DL) provides a powerful framework for extracting such information from existin...

Artificial Intelligence for Medical Image Analysis: A Guide for Authors and Reviewers.

AJR. American journal of roentgenology
OBJECTIVE: The purpose of this article is to highlight best practices for writing and reviewing articles on artificial intelligence for medical image analysis.

AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy.

Medical physics
PURPOSE: Radiation therapy (RT) is a common treatment option for head and neck (HaN) cancer. An important step involved in RT planning is the delineation of organs-at-risks (OARs) based on HaN computed tomography (CT). However, manually delineating O...

Automatic interpretation of otoliths using deep learning.

PloS one
The age structure of a fish population has important implications for recruitment processes and population fluctuations, and is a key input to fisheries-assessment models. The current method of determining age structure relies on manually reading age...

Micro-Net: A unified model for segmentation of various objects in microscopy images.

Medical image analysis
Object segmentation and structure localization are important steps in automated image analysis pipelines for microscopy images. We present a convolution neural network (CNN) based deep learning architecture for segmentation of objects in microscopy i...

Unsupervised Person Re-Identification by Deep Asymmetric Metric Embedding.

IEEE transactions on pattern analysis and machine intelligence
Person re-identification (Re-ID) aims to match identities across non-overlapping camera views. Researchers have proposed many supervised Re-ID models which require quantities of cross-view pairwise labelled data. This limits their scalabilities to ma...

Patient 3D body pose estimation from pressure imaging.

International journal of computer assisted radiology and surgery
PURPOSE: In-bed motion monitoring has become of great interest for a variety of clinical applications. Image-based approaches could be seen as a natural non-intrusive approach for this purpose; however, video devices require special challenging setti...

An overview of deep learning in medical imaging focusing on MRI.

Zeitschrift fur medizinische Physik
What has happened in machine learning lately, and what does it mean for the future of medical image analysis? Machine learning has witnessed a tremendous amount of attention over the last few years. The current boom started around 2009 when so-called...