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Journal of Imaging, Volume 6, Issue 12

December 2020 - 16 articles

Cover Story: X-ray plenoptic cameras acquire multi-view X-ray transmission images in a single exposure (light field). Their development is challenging: designs have appeared only recently, and they are still affected by important limitations. Concurrently, the lack of available real X-ray light field data hinders dedicated algorithmic development. We present a physical emulation setup for rapidly exploring the parameter space of both existing and conceptual camera designs. This will assist and accelerate the design of X-ray plenoptic imaging solutions, and allow one to generate unlimited real X-ray plenoptic data. We also demonstrate that X-ray light fields enable the reconstruction of sharp spatial structures in three dimensions from single-shot data. This confirms that X-ray plenoptic cameras will lead to breakthroughs in a wide range of application areas. View this paper.

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Article

12 Citations

3,437 Views

17 Pages

3D Non-Local Neural Network: A Non-Invasive Biomarker for Immunotherapy Treatment Outcome Prediction. Case-Study: Metastatic Urothelial Carcinoma

Francesco Rundo,
Giuseppe Luigi Banna,
Luca Prezzavento,
Francesca Trenta,
Sabrina Conoci and
Sebastiano Battiato

J. Imaging2020, 6(12), 133;https://doi.org/10.3390/jimaging6120133

3 December 2020

Immunotherapy is regarded as one of the most significant breakthroughs in cancer treatment. Unfortunately, only a small percentage of patients respond properly to the treatment. Moreover, to date, there are no efficient bio-markers able to early disc...

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Article

10 Citations

5,598 Views

28 Pages

Task-Driven Learned Hyperspectral Data Reduction Using End-to-End Supervised Deep Learning

Mathé T. Zeegers,
Daniël M. Pelt,
Tristan van Leeuwen,
Robert van Liere and
Kees Joost Batenburg

J. Imaging2020, 6(12), 132;https://doi.org/10.3390/jimaging6120132

2 December 2020

An important challenge in hyperspectral imaging tasks is to cope with the large number of spectral bins. Common spectral data reduction methods do not take prior knowledge about the task into account. Consequently, sparsely occurring features that ma...

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Review

130 Citations

17,981 Views

38 Pages

A Survey of Deep Learning for Lung Disease Detection on Medical Images: State-of-the-Art, Taxonomy, Issues and Future Directions

Stefanus Tao Hwa Kieu,
Abdullah Bade,
Mohd Hanafi Ahmad Hijazi and
Hoshang Kolivand

J. Imaging2020, 6(12), 131;https://doi.org/10.3390/jimaging6120131

1 December 2020

The recent developments of deep learning support the identification and classification of lung diseases in medical images. Hence, numerous work on the detection of lung disease using deep learning can be found in the literature. This paper presents a...

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Article

19 Citations

5,743 Views

20 Pages

FACS-Based Graph Features for Real-Time Micro-Expression Recognition

Adamu Muhammad Buhari,
Chee-Pun Ooi,
Vishnu Monn Baskaran,
Raphaël C. W. Phan,
KokSheik Wong and
Wooi-Haw Tan

J. Imaging2020, 6(12), 130;https://doi.org/10.3390/jimaging6120130

30 November 2020

Several studies on micro-expression recognition have contributed mainly to accuracy improvement. However, the computational complexity receives lesser attention comparatively and therefore increases the cost of micro-expression recognition for real-t...

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Article

13 Citations

4,031 Views

11 Pages

A Fast Neutron Radiography System Using a High Yield Portable DT Neutron Source

David L. Williams,
Craig M. Brown,
David Tong,
Alexander Sulyman and
Charles K. Gary

J. Imaging2020, 6(12), 128;https://doi.org/10.3390/jimaging6120128

26 November 2020

Resolution measurements were made using 14.1 MeV neutrons from a high-yield, portable DT neutron generator and a neutron camera based on a scintillation screen viewed by a digital camera. Resolution measurements were made using a custom-built, plasti...

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Article

27 Citations

3,534 Views

15 Pages

Bucket of Deep Transfer Learning Features and Classification Models for Melanoma Detection

Mario Manzo and
Simone Pellino

J. Imaging2020, 6(12), 129;https://doi.org/10.3390/jimaging6120129

26 November 2020

Malignant melanoma is the deadliest form of skin cancer and, in recent years, is rapidly growing in terms of the incidence worldwide rate. The most effective approach to targeted treatment is early diagnosis. Deep learning algorithms, specifically co...

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