Journal of Healthcare Engineering

Machine Learning for Medical Imaging


Publishing date
01 Apr 2019
Status
Published
Submission deadline
23 Nov 2018

Lead Editor

1Amazon.com, Cambridge, USA

2Icahn School of Medicine at Mount Sinai, New York City, USA

3Dalian University of Technology, Dalian, China

4Harvard Medical School, Boston, USA


Machine Learning for Medical Imaging

Description

Machine learning methods have been successfully applied to many applications. One such application that has received considerable attention in recent years is medical imaging. With improvements in computer hardware and the availability of enormous amounts of data, machine learning approaches, such as deep learning, simplify feature engineering and have shown great promise in medical image analysis. However, there are still many remaining challenges, for example, inconsistency in data format and lack of labeled training data that need to be addressed.

The aim of this special issue is to highlight state-of-the-art research on medical imaging with machine learning methods. High-quality research articles and reviews are welcome. The latest progress on medical image processing with deep learning is of special interest.

Potential topics include but are not limited to the following:

  • Machine Learning for Medical image analysis
  • Multitask learning for Medical image reconstruction
  • Fuzzy learning method in Disease identification/diagnosis
  • Multimodal Machine learning for data fusion in medical imaging
  • Ensemble learning for Real-time health monitoring systems
  • Supervised, unsupervised, and semisupervised learning for medical imaging
  • Deep learning for medical image processing

Articles

  • Special Issue
  • - Volume 2019
  • - Article ID 9874591
  • - Editorial

Machine Learning for Medical Imaging

Geng-Shen Fu | Yuri Levin-Schwartz | ... | Da Zhang
  • Special Issue
  • - Volume 2019
  • - Article ID 9360941
  • - Research Article

Convolutional Neural Networks for the Segmentation of Microcalcification in Mammography Imaging

Gabriele Valvano | Gianmarco Santini | ... | Daniele Della Latta
  • Special Issue
  • - Volume 2019
  • - Article ID 2492719
  • - Research Article

Alzheimer’s Disease Diagnosis Based on Cortical and Subcortical Features

Yubraj Gupta | Kun Ho Lee | ... | Goo-Rak Kwon
  • Special Issue
  • - Volume 2019
  • - Article ID 4321645
  • - Research Article

Dynamic Regulation of Level Set Parameters Using 3D Convolutional Neural Network for Liver Tumor Segmentation

Zhuofu Deng | Qingzhe Guo | Zhiliang Zhu
  • Special Issue
  • - Volume 2019
  • - Article ID 4061313
  • - Research Article

Glaucoma Diagnosis with Machine Learning Based on Optical Coherence Tomography and Color Fundus Images

Guangzhou An | Kazuko Omodaka | ... | Toru Nakazawa
  • Special Issue
  • - Volume 2019
  • - Article ID 5156416
  • - Research Article

Improving Accuracy of Lung Nodule Classification Using Deep Learning with Focal Loss

Giang Son Tran | Thi Phuong Nghiem | ... | Jean-Christophe Burie
  • Special Issue
  • - Volume 2019
  • - Article ID 1075434
  • - Research Article

Automated Segmentation of Colorectal Tumor in 3D MRI Using 3D Multiscale Densely Connected Convolutional Neural Network

Mumtaz Hussain Soomro | Matteo Coppotelli | ... | Andrea Laghi
Journal of Healthcare Engineering
 Journal metrics
Acceptance rate37%
Submission to final decision99 days
Acceptance to publication48 days
CiteScore2.600
Impact Factor1.803
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