Sidelobe considerations in AOTF imaging

Gupta, Neelam; Suhre, Dennis R.

doi:10.1117/12.2252277

Cited by 2 publications

(1 citation statement)

References 40 publications

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“…At the same time, the incident and diffracted light wave vectors are parallel to each other in the tangent of the corresponding doctoral surface, which satisfies the condition of momentum tangent parallelism. When the incident angle changes slightly, the change of refractive index with the angle of birefringence can compensate for the momentum mismatch caused by the angle change [4][5][6] . This forms the theoretical basis of large angle aperture AOTF.…”

Section: Principlementioning

confidence: 99%

Hyperspectral microscopic imaging of skin squamous cell carcinoma

Sheng¹,

Zhang²,

Qiu³

et al. 2019

14th National Conference on Laser Technology and Optoelectronics (LTO 2019)

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Acousto-optic tunable filter (AOTF) is a new type of light splitter with fast tuning, stable structure and portability. In this paper, a hyperspectral microscopic imaging system is constructed by combining non-collinear AOTF with optical inverted microscopy. The feasibility of data augmentation based on hyperspectral images for object detection of skin squamous cell carcinoma is studied. The hyperspectral images collected from unstained sections of skin squamous cell carcinoma are processed into dataset. At the same time, the mature open source object detection model is selected and trained for 20,000 times. Using the trained model to detect the lesion area of other unstained sections, it is found that the model trained by hyperspectral image dataset has a good ability to distinguish the non-lesion area, and there is no false detection. And the model has a relatively accurate detection ability for large lesion area, but the results of the model for small lesion area are not ideal. After analysis, it is considered that the number of samples can be increased firstly, especially in small lesions, and the same to the hyperspectral images. In addition, the model for lesion detection can be further optimized. By increasing the complexity of the model, the model can learn more details and information in the image during the training process. The preliminary results of the experiment prove that hyperspectral imaging is feasible for data augmentation of lesion object detection dataset. This paper provides a new method for the object detection data augmentation of skin squamous cell carcinoma.

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Section: Principlementioning

confidence: 99%

Hyperspectral microscopic imaging of skin squamous cell carcinoma

Sheng¹,

Zhang²,

Qiu³

et al. 2019

14th National Conference on Laser Technology and Optoelectronics (LTO 2019)

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Ray tracing method for removing sidelobe laser interference in AOTF-based hyperspectral imaging

Shi

Wang

et al. 2021

Appl. Opt.

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The sidelobe phenomenon of acousto-optic tunable filter (AOTF)-based hyperspectral imaging is the result of the phase mismatching condition, which will reduce the quality of hyperspectral imaging data. This phenomenon can be observed in two specified scenes, namely, high brightness panchromatic target imaging and high brightness monochromatic target imaging. In this paper, the acousto-optic interaction in these two scenes is discussed using the phase matching condition. As a follow-up work of the previous related research, this paper studies laser interference in AOTF imaging, which is a typical example of the second case. A method to remove laser sidelobes in AOTF-based hyperspectral imaging is proposed, which combines a series of procedures including laser point extraction, reverse imaging before AOTF, ray tracing in AOTF, forward imaging process after AOTF, and laser elimination. Experimental results have verified the effectiveness of the proposed method.

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Sidelobe considerations in AOTF imaging

Cited by 2 publications

References 40 publications

Hyperspectral microscopic imaging of skin squamous cell carcinoma

Hyperspectral microscopic imaging of skin squamous cell carcinoma

Ray tracing method for removing sidelobe laser interference in AOTF-based hyperspectral imaging

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