Roadmap on Recent Progress in FINCH Technology

Rosen, Joseph; Alford, Simon; Anand, Vijayakumar; Art, Jonathan; Bouchal, Petr; Bouchal, Zdeněk; Erdenebat, Munkh Uchral; Huang, Lingling; Ishii, Ayumi; Juodkazis, Saulius; Kim, Nam; Kner, Peter; Koujin, Takako; Kozawa, Yuichi; Dong, Liang; Liu, Jun; Mann, Christopher; Marar, Abhijit; Matsuda, Atsushi; Nobukawa, Teruyoshi; Nomura, Takanori; Oi, Ryutaro; Potcoava, Mariana; Tahara, Tatsuki; Thanh, Bang Le; Zhou, Hongqiang

doi:10.3390/jimaging7100197

Cited by 57 publications

(28 citation statements)

References 134 publications

(249 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Compact IDH systems have been proposed using various IDH techniques, which is described in this review and ref. (Rosen et al, 2021). It is now possible to realize portable holographic imaging systems for sensing outdoor 3D scenes with IDH techniques.…”

Section: Discussionmentioning

confidence: 99%

“…Experiments on HE-stained mouse kidney cells were successfully conducted. Then, PSF improvement in full-color incoherent imaging was achieved (Rosen et al, 2021). The CCS-IDH system was also combined with a fluorescence microscope, and color-multiplexed holographic fluorescence microscopy was presented (Tahara et al, 2021a;Tahara et al, 2021b).…”

Section: Ccs Incoherent Digital Holographic Microscopymentioning

confidence: 99%

See 1 more Smart Citation

Review of Incoherent Digital Holography: Applications to Multidimensional Incoherent Digital Holographic Microscopy and Palm-Sized Digital Holographic Recorder—Holosensor

Tahara

2022

Front. Photon.

Self Cite

View full text Add to dashboard Cite

We review advancements in incoherent digital holography (IDH) with an image sensor and its applications to multidimensional microscopy and a palm-sized hologram recorder termed “holosensor”. There are two types of representative IDH technique: IDH with a structured illumination and a single photodetector termed optical scanning holography and self-interference IDH. The latter IDH is a technique to obtain an incoherent digital hologram by modulating an incoherent light wave between an object and an image sensor. Multidimensional information such as three-dimensional space and wavelengths is simultaneously recorded without changing optical filters by introducing interferometric techniques invented in laser holography. Applications to high-speed color-multiplexed holographic fluorescence microscopy, single-shot incoherent full-color holographic microscopy with white light, and a palm-sized multidimensional incoherent hologram recorder have been developed using multidimensional IDH systems. Schematics and experimental results obtained using IDH techniques, incoherent holographic microscopy systems, and compact IDH systems are introduced.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Ccs Incoherent Digital Holographic Microscopymentioning

confidence: 99%

Review of Incoherent Digital Holography: Applications to Multidimensional Incoherent Digital Holographic Microscopy and Palm-Sized Digital Holographic Recorder—Holosensor

Tahara

2022

Front. Photon.

Self Cite

View full text Add to dashboard Cite

show abstract

“…This collective effort of computational and optical transformations expands the imaging capability to multiple dimensions beyond the limits of the direct imager [ 2 ]. In recent years, much attention has been given to the development of spatially incoherent imaging techniques in indirect imaging mode due to the multitude of useful properties they exhibit, such as high imaging resolution and low imaging noises [ 2 , 3 , 4 , 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

“…Incoherent imaging techniques can be further classified into interference-based [ 2 , 5 ] and noninterferometric [ 6 ]. Many of the current interference-based incoherent imaging methods employ the Fresnel incoherent correlation holography (FINCH) architecture to record incoherent digital holograms [ 5 , 7 , 8 , 9 , 10 ]. An alternative method for recording incoherent digital holograms is scanning holography [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Reconstruction of Images from Patterns Generated by Deterministic or Random Optical Masks—Concepts and Review of Research

et al. 2022

Self Cite

View full text Add to dashboard Cite

Indirect-imaging methods involve at least two steps, namely optical recording and computational reconstruction. The optical-recording process uses an optical modulator that transforms the light from the object into a typical intensity distribution. This distribution is numerically processed to reconstruct the object’s image corresponding to different spatial and spectral dimensions. There have been numerous optical-modulation functions and reconstruction methods developed in the past few years for different applications. In most cases, a compatible pair of the optical-modulation function and reconstruction method gives optimal performance. A new reconstruction method, termed nonlinear reconstruction (NLR), was developed in 2017 to reconstruct the object image in the case of optical-scattering modulators. Over the years, it has been revealed that the NLR can reconstruct an object’s image modulated by an axicons, bifocal lenses and even exotic spiral diffractive elements, which generate deterministic optical fields. Apparently, NLR seems to be a universal reconstruction method for indirect imaging. In this review, the performance of NLR isinvestigated for many deterministic and stochastic optical fields. Simulation and experimental results for different cases are presented and discussed.

show abstract

“…Ophthalmologists can detect AMD-related lesions through a variety of methods with the continuous development of imaging technology [ 9 , 10 , 11 , 12 ]. Optical coherence tomography (OCT) uses the basic principle of a weak coherence interferometer to carry out high-resolution cross-sectional tomography of the internal microstructure of materials or biological systems [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Automatic Detection of Age-Related Macular Degeneration Based on Deep Learning and Local Outlier Factor Algorithm

Zhou

Zou

2022

Diagnostics

View full text Add to dashboard Cite

Age-related macular degeneration (AMD) is a retinal disorder affecting the elderly, and society’s aging population means that the disease is becoming increasingly prevalent. The vision in patients with early AMD is usually unaffected or nearly normal but central vision may be weakened or even lost if timely treatment is not performed. Therefore, early diagnosis is particularly important to prevent the further exacerbation of AMD. This paper proposed a novel automatic detection method of AMD from optical coherence tomography (OCT) images based on deep learning and a local outlier factor (LOF) algorithm. A ResNet-50 model with L2-constrained softmax loss was retrained to extract features from OCT images and the LOF algorithm was used as the classifier. The proposed method was trained on the UCSD dataset and tested on both the UCSD dataset and Duke dataset, with an accuracy of 99.87% and 97.56%, respectively. Even though the model was only trained on the UCSD dataset, it obtained good detection accuracy when tested on another dataset. Comparison with other methods also indicates the efficiency of the proposed method in detecting AMD.

show abstract

Roadmap on Recent Progress in FINCH Technology

Cited by 57 publications

References 134 publications

Review of Incoherent Digital Holography: Applications to Multidimensional Incoherent Digital Holographic Microscopy and Palm-Sized Digital Holographic Recorder—Holosensor

Review of Incoherent Digital Holography: Applications to Multidimensional Incoherent Digital Holographic Microscopy and Palm-Sized Digital Holographic Recorder—Holosensor

Nonlinear Reconstruction of Images from Patterns Generated by Deterministic or Random Optical Masks—Concepts and Review of Research

Automatic Detection of Age-Related Macular Degeneration Based on Deep Learning and Local Outlier Factor Algorithm

Contact Info

Product

Resources

About