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Journal of Imaging, Volume 9, Issue 8

August 2023 - 17 articles

Cover Story: The k-space sampling trajectory heavily affects the performance of compressed sensing image reconstruction models. Still, knowledge on the relative performance of the well-known compressed sensing models with three-dimensional radial trajectories is lacking. Here, we utilize radial three-dimensional T1 mapping to compare the performance of total variation, locally low rank, and Huber penalty function approaches. Graphics processing unit implementation of a preconditioned primal-dual proximal splitting algorithm is used to solve the large-scale optimization problems in feasible time. Spatial total variation combined with locally low rank was the best performing model. However, differences between the models are not necessarily large. All of the source code is freely available. View this paper
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Articles (17)

  • Article
  • Open Access
11 Citations
4,062 Views
15 Pages

18 August 2023

A content-based image retrieval system, as an Indonesian traditional woven fabric knowledge base, can be useful for artisans and trade promotions. However, creating an effective and efficient retrieval system is difficult due to the lack of an Indone...

  • Article
  • Open Access
7 Citations
3,554 Views
11 Pages

Accuracy of Intra-Oral Radiography and Cone Beam Computed Tomography in the Diagnosis of Buccal Bone Loss

  • Véronique Christiaens,
  • Ruben Pauwels,
  • Bassant Mowafey and
  • Reinhilde Jacobs

17 August 2023

Background: The use of cone beam computed tomography (CBCT) in dentistry started in the maxillofacial field, where it was used for complex and comprehensive treatment planning. Due to the use of reduced radiation dose compared to a computed tomograph...

  • Article
  • Open Access
42 Citations
3,073 Views
15 Pages

MRI-Based Effective Ensemble Frameworks for Predicting Human Brain Tumor

  • Farhana Khan,
  • Shahnawaz Ayoub,
  • Yonis Gulzar,
  • Muneer Majid,
  • Faheem Ahmad Reegu,
  • Mohammad Shuaib Mir,
  • Arjumand Bano Soomro and
  • Osman Elwasila

16 August 2023

The diagnosis of brain tumors at an early stage is an exigent task for radiologists. Untreated patients rarely survive more than six months. It is a potential cause of mortality that can occur very quickly. Because of this, the early and effective di...

  • Article
  • Open Access
5 Citations
2,726 Views
15 Pages

16 August 2023

Thangka images exhibit a high level of diversity and richness, and the existing deep learning-based image captioning methods generate poor accuracy and richness of Chinese captions for Thangka images. To address this issue, this paper proposes a Sema...

  • Article
  • Open Access
9 Citations
3,599 Views
18 Pages

Vision Transformer Customized for Environment Detection and Collision Prediction to Assist the Visually Impaired

  • Nasrin Bayat,
  • Jong-Hwan Kim,
  • Renoa Choudhury,
  • Ibrahim F. Kadhim,
  • Zubaidah Al-Mashhadani,
  • Mark Aldritz Dela Virgen,
  • Reuben Latorre,
  • Ricardo De La Paz and
  • Joon-Hyuk Park

15 August 2023

This paper presents a system that utilizes vision transformers and multimodal feedback modules to facilitate navigation and collision avoidance for the visually impaired. By implementing vision transformers, the system achieves accurate object detect...

  • Article
  • Open Access
2 Citations
2,629 Views
13 Pages

Selective Optical Imaging for Detection of Bacterial Biofilms in Tissues

  • Michael Okebiorun,
  • Cody Oberbeck,
  • Cameron Waite,
  • Samuel Clark,
  • Dalton Miller,
  • Elisa H. Barney Smith,
  • Kenneth A. Cornell and
  • Jim Browning

15 August 2023

Significance: The development of an imaging technique to accurately identify biofilm regions on tissues and in wounds is crucial for the implementation of precise surface-based treatments, leading to better patient outcomes and reduced chances of inf...

  • Article
  • Open Access
2 Citations
2,488 Views
14 Pages

Biased Deep Learning Methods in Detection of COVID-19 Using CT Images: A Challenge Mounted by Subject-Wise-Split ISFCT Dataset

  • Shiva Parsarad,
  • Narges Saeedizadeh,
  • Ghazaleh Jamalipour Soufi,
  • Shamim Shafieyoon,
  • Farzaneh Hekmatnia,
  • Andrew Parviz Zarei,
  • Samira Soleimany,
  • Amir Yousefi,
  • Hengameh Nazari and
  • Pegah Torabi
  • + 5 authors

Accurate detection of respiratory system damage including COVID-19 is considered one of the crucial applications of deep learning (DL) models using CT images. However, the main shortcoming of the published works has been unreliable reported accuracy...

  • Article
  • Open Access
22 Citations
4,456 Views
15 Pages

Enhancing Fingerprint Liveness Detection Accuracy Using Deep Learning: A Comprehensive Study and Novel Approach

  • Deep Kothadiya,
  • Chintan Bhatt,
  • Dhruvil Soni,
  • Kalpita Gadhe,
  • Samir Patel,
  • Alessandro Bruno and
  • Pier Luigi Mazzeo

Liveness detection for fingerprint impressions plays a role in the meaningful prevention of any unauthorized activity or phishing attempt. The accessibility of unique individual identification has increased the popularity of biometrics. Deep learning...

  • Article
  • Open Access
2,319 Views
18 Pages

Target Design in SEM-Based Nano-CT and Its Influence on X-ray Imaging

  • Jonas Fell,
  • Felix Wetzler,
  • Michael Maisl and
  • Hans-Georg Herrmann

Nano-computed tomography (nano-CT) based on scanning electron microscopy (SEM) is utilized for multimodal material characterization in one instrument. Since SEM-based CT uses geometrical magnification, X-ray targets can be adapted without any further...

  • Article
  • Open Access
1,600 Views
14 Pages

A 3D film pattern image was recently developed for marketing purposes, and an inspection method is needed to evaluate the quality of the pattern for mass production. However, due to its recent development, there are limited methods to inspect the 3D...

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J. Imaging - ISSN 2313-433X