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Journal of Imaging, Volume 7, Issue 2

February 2021 - 29 articles

Cover Story: Nuclear magnetic resonance (NMR) relaxometry is an essential non-invasive and non-destructive tool to study porous media’s properties and the saturating fluids’ behavior, with a wide range of applications: cements, reservoir rocks, foods. However, especially for two-dimensional NMR (2DNMR) experiments, long inversion times caused by the large data size, together with high sensitivity of the solution to data noise, still represent significant issues. We present a 2DNMR data inversion method combining the truncated singular value decomposition and Tikhonov regularization to accelerate the inversion process and reduce the sensitivity to the regularization parameter value. The quality of 2DNMR relaxation time distributions and the increased computational efficiency obtained on synthetic and real 2DNMR data motivate the extension of such an approach to higher-dimensional problems. View this paper
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Articles (29)

  • Review
  • Open Access
6 Citations
4,077 Views
17 Pages

Performance Overview of the Latest Video Coding Proposals: HEVC, JEM and VVC

  • Miguel O. Martínez-Rach,
  • Héctor Migallón,
  • Otoniel López-Granado,
  • Vicente Galiano and
  • Manuel P. Malumbres

22 February 2021

The audiovisual entertainment industry has entered a race to find the video encoder offering the best Rate/Distortion (R/D) performance for high-quality high-definition video content. The challenge consists in providing a moderate to low computationa...

  • Article
  • Open Access
11 Citations
3,832 Views
23 Pages

22 February 2021

In this paper, we provide an overview on the foundation and first results of a very recent quantum theory of color perception, together with novel results about uncertainty relations for chromatic opposition. The major inspiration for this model is t...

  • Article
  • Open Access
3 Citations
3,148 Views
18 Pages

Data-Driven Regularization Parameter Selection in Dynamic MRI

  • Matti Hanhela,
  • Olli Gröhn,
  • Mikko Kettunen,
  • Kati Niinimäki,
  • Marko Vauhkonen and
  • Ville Kolehmainen

20 February 2021

In dynamic MRI, sufficient temporal resolution can often only be obtained using imaging protocols which produce undersampled data for each image in the time series. This has led to the popularity of compressed sensing (CS) based reconstructions. One...

  • Article
  • Open Access
25 Citations
6,350 Views
13 Pages

17 February 2021

We present a sample-efficient image segmentation method using active learning, we call it Active Bayesian UNet, or AB-UNet. This is a convolutional neural network using batch normalization and max-pool dropout. The Bayesian setup is achieved by explo...

  • Article
  • Open Access
14 Citations
5,204 Views
10 Pages

Accelerating 3D Medical Image Segmentation by Adaptive Small-Scale Target Localization

  • Boris Shirokikh,
  • Alexey Shevtsov,
  • Alexandra Dalechina,
  • Egor Krivov,
  • Valery Kostjuchenko,
  • Andrey Golanov,
  • Victor Gombolevskiy,
  • Sergey Morozov and
  • Mikhail Belyaev

13 February 2021

The prevailing approach for three-dimensional (3D) medical image segmentation is to use convolutional networks. Recently, deep learning methods have achieved human-level performance in several important applied problems, such as volumetry for lung-ca...

  • Article
  • Open Access
11 Citations
4,102 Views
21 Pages

13 February 2021

Digital Breast Tomosynthesis is an X-ray imaging technique that allows a volumetric reconstruction of the breast, from a small number of low-dose two-dimensional projections. Although it is already used in the clinical setting, enhancing the quality...

  • Article
  • Open Access
7 Citations
3,335 Views
19 Pages

11 February 2021

The popularity of social networks (SNs), amplified by the ever-increasing use of smartphones, has intensified online cybercrimes. This trend has accelerated digital forensics through SNs. One of the areas that has received lots of attention is camera...

  • Review
  • Open Access
45 Citations
8,356 Views
14 Pages

Radiomics and Prostate MRI: Current Role and Future Applications

  • Giuseppe Cutaia,
  • Giuseppe La Tona,
  • Albert Comelli,
  • Federica Vernuccio,
  • Francesco Agnello,
  • Cesare Gagliardo,
  • Leonardo Salvaggio,
  • Natale Quartuccio,
  • Letterio Sturiale and
  • Alessandro Stefano
  • + 4 authors

11 February 2021

Multiparametric prostate magnetic resonance imaging (mpMRI) is widely used as a triage test for men at a risk of prostate cancer. However, the traditional role of mpMRI was confined to prostate cancer staging. Radiomics is the quantitative extraction...

  • Article
  • Open Access
10 Citations
7,732 Views
11 Pages

10 February 2021

The aim of this paper is to investigate the clinical utility of the application of deep learning denoise algorithms on standard wide-field Optical Coherence Tomography Angiography (OCT-A) images. This was a retrospective case-series assessing forty-n...

  • Article
  • Open Access
25 Citations
7,020 Views
14 Pages

Domain Adaptation for Medical Image Segmentation: A Meta-Learning Method

  • Penghao Zhang,
  • Jiayue Li,
  • Yining Wang and
  • Judong Pan

10 February 2021

Convolutional neural networks (CNNs) have demonstrated great achievement in increasing the accuracy and stability of medical image segmentation. However, existing CNNs are limited by the problem of dependency on the availability of training data owin...

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J. Imaging - ISSN 2313-433XCreative Common CC BY license