Publications

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2024

26. Ganjee, Razieh, Bingjie Wang, Lingyun Wang, Chengcheng Zhao, José-Alain Sahel, and Shaohua Pi*. "BreakNet: discontinuity-resilient multi-scale transformer segmentation of retinal layers." Biomedical Optics Express 15, no. 12 (2024): 6725-6738.

*First deep learning segmentation model focus on addressing shadow breaks

We present BreakNet, a multi-scale Transformer segmentation model designed to address boundary discontinuities caused by shadow artifacts.

25. Pi Shaohua*, Ganjee Razieh, Wang Lingyun, Arbuckle Riley, Zhao Chengcheng, Sahel José-Alain, Wang Bingjie, and Chen Yuanyuan. "Fully automated OCT-based tissue screening system." Optics Letters 49(16), pp.4481-4484.

*First dedicated OCT for living tissue imaging

customize a motorized platform for automated OCT scan acquisition in living tissue and develop Transformer algorithms for fast readouts.

Fig. 1 (A) schematic diagram, (B) photograph, and (C) pipeline of the the proposed fully automated OCT for living tissue screening.

24. Mehta, Kamakshi, Marwa Daghsni, Reza Raeisossadati, Zhongli Xu, Emily Davis, Abigail Naidich, Bingjie Wang, Tao Shiyue, Pi Shaohua, Chen Wei, Kostka, Dennis, Liu Silvia, Gross Jeffrey, Kuwajima Takaaki, Aldiri Issam. "A cis-regulatory module underlies retinal ganglion cell genesis and axonogenesis." Cell Reports. 2024 Jun 25;43(6).

Collaborative paper with Dr. Issam Aldiri on RGC development

Provide OCT imaging for the Atoh7 mice models

23. Wang Lingyun, Sahel José-Alain, and Pi Shaohua*. "Sub2Full: split spectrum to boost OCT despeckling without clean data." Optics Letters, 49(11), pp.3062-3065.

*The lab's first OCT despecking research paper

Invent a new Sub2Full strategy to achieve outperformed denoising performance over Noise2Noise and Noise2Void in OCT

Fig. 1 The zoom-in view of enhanced B-scan image from a single vis-OCT volume of rat retina showing the sub-laminar structure in outer retinal region. (b) Diagram of the outer retina. (c) TEM image of a rat retina.

22. Wang Bingjie, Ganjee Razieh, Khandaker Irona, Flohr Keevon, He Yuanhang, Li Guang, Wesalo Joshua, Sahel José-Alain, Da Silva Susana, and Pi Shaohua*. "Deep learning based characterization of human organoids using optical coherence tomography." Biomedical Optics Express, 15(5), pp.3112-3127.

*The lab's first research paper on deep learning and organoids

Develop a deep learning platform called OrgSegNet for automated characterization of human retinal and cardiac organoids.

Fig. 1 The architecture of the proposed OrgSegNet for deep learning segmentation of organoid tissue and internal structure in OCT B-scan images. A cardiac organoid is shown as a representative example.

21. Bingjie Wang, Riley K. Arbuckle, Katherine A. Davoli, Owen D. Clinger, Richard Brown, José-Alain Sahel, Yuanyuan Chen, and Pi Shaohua*. "Compensation of inner retina to early-stage photoreceptor degeneration in a RhoP23H/+ mouse model of retinitis pigmentosa." Experimental Eye Research, p.109826.

*The lab's first research paper on OCT imaging of RhoP23H/+ mouse model of retinitis pigmentosa

Quantitative measurement of compensation of inner retinal to photoreceptor degeneration with validations in histology and ERG.

Fig. 1 Statistical analysis of RhoP23H/+ vs. WT retinae (A) Comparisons of retinal layer thicknesses in OCT. (B) The associations of INL thickness (red squares) and total retina thickness (green circles) to ONL thickness from RhoP23H/+ mouse retinae at P71 were measured in histology images. (C) Scotopic b-: a-wave ratios at various flash intensities in ERG.

2023

20. Tae-Hoon Kim*, Yannis M Paulus*, Bernhard Baumann*, Pengfei Zhang*, Shaohua Pi*. "In vivo retinal imaging in animal models." Frontiers in Ophthalmology 3, (2023): 1309894.

*Dr. Pi's first editorial article

Summarize the research papers published in the special issue "In vivo retinal imaging in animal models"

19. Wang Bingjie, Richard Brown, Jay Chhablani, and Shaohua Pi*. "Volumetrically tracking retinal and choroidal structural changes in central serous chorioretinopathy." Biomedical Optics Express 14, no. 10 (2023): 5528-5538. [ARVO] [bioRxiv]

*The lab's first independent research paper

First step to fast and accurate assessment of retinal disease progression and/or treatment efficacy in 3-D using OCT

Fig. 1 Representative 3-D change map detection for the left eye of a 57-year-old man with central serous chorioretinopathy (CSCR) who underwent photodynamic therapy after a baseline visit. (A) Baseline visit B-scan displaying accumulated fluid in the subretinal space. (B) B-scan from the follow-up visit showing the resolved fluid. (C) Overlay of the B-scans after registration. (D) Detected 3-D change map (cyan) overlaid with baseline and follow-up B-scans. (E) Detected 3-D change map (cyan) overlaid with baseline and follow-up volumes.

18. Yam, Gary Hin-Fai, Shaohua Pi, Yiqin Du, and Jodhbir S. Mehta. "Posterior corneoscleral limbus: Architecture, stem cells, and clinical implications." Progress in Retinal and Eye Research (2023): 101192.

*The lab's first collaborative review paper on PRER

17. Shaohua Pi, Bingjie Wang, Min Gao, William Cepurna, Dinana C. Lozano, John C. Morrison, and Yali Jia. "Longitudinal Observation of Retinal Response to Optic Nerve Transection in Rats Using Visible Light Optical Coherence Tomography" Investigative Ophthalmology & Visual Science 64, no 4 (2023): 17-17.

First paper to identify retinal response to ONT rats using vis-OCT

Fig. 1 En face structural images projected from the total retina slab and NFL slab, as well as the en face angiographic images projected from SVP, ICP, and DCP plexuses.

Fig. 2 Suspect immune response cells appeared in rat eyes at 1-week post-ONT, as captured by the high-resolution vis-OCT and visualized in the en face projection images of vitreous slabs. In contrast, these cells were not observed before ONT.

2022

16. Xiang Wei, Tristan T. Hormel, Shaohua Pi, Bingjie Wang, John C. Morrison, and Yali Jia. "Wide-field sensorless adaptive optics swept-source optical coherence tomographic angiography in rodents." Optics Letters 47, no. 19 (2022): 5060-5063.

15. Shaohua Pi, Tristan T. Hormel, Bingjie Wang, Steven T. Bailey, Thomas S. Hwang, David Huang, John C. Morrison, and Yali Jia, "Volume-based, layer-independent, disease-agnostic detection of abnormal retinal reflectivity, nonperfusion, and neovascularization using structural and angiographic OCT," Biomed. Opt. Express 13, 4889-4906 (2022).

First steps to identify 3-D map of retinal ischemia and establish universal pathology index

Fig. 1 Demonstration of OCT scan registration in different subjects. (A) Lateral registration was achieved by foveal center alignment in a 9×9-mm image, with the nasal side flipped in the left eyes to match with the right eyes. (B) Axial registration is achieved by axially normalizing the A-lines according to percent retinal depth.

Fig. 2 Demonstration of 3-D detection of nonperfusion. The perfusion volume simulated by convoluting the angiogram volume with 3-D Gaussian kernel, and then compared between reference and diseased retinas using Eq. (2) to calculate the 3-D nonperfusion map. The 3-D nonperfusion map is color-coded by percent retinal depth (ILM: 0, BM: 100).

Fig. 3 Diagnostic power of various pathology indexes to differentiate non-referable DR from referable DR subjects. The pathology index for each clinical feature was calculated as the decibel ratio of the averaged deviation magnitude from a target retinal scan (Pd) to baselines (Ph) from healthy subjects. (A) The combined pathology index achieved an R=0.95 Spearman correlation coefficient with the DR severity. The black dotted line indicates a pathology index cut-off PI=6 corresponding to the best diagnostic point in B. (B) Receiver operating characteristic curves for the pathology indexes of each clinical feature, and the combined one for referable vs. non-referable DR classification. The optimal operating point of the ROC curve for the averaged PI was determined as 1-specificity= 0.28 and sensitivity=0.87, output from the parameter OPTROCPT of the MATLAB function perfcurve( ).

2021

14. Yukun Guo, Tristan T. Hormel, Shaohua Pi, Xiang Wei, Min Gao, John C. Morrison, and Yali Jia. "An end-to-end network for segmenting the vasculature of three retinal capillary plexuses from OCT angiographic volumes." Biomedical Optics Express 12, no. 8 (2021): 4889-4900.

13. Qisheng You, Ou Tan, Shaohua Pi, Liang Liu, Ping Wei, Aiyin Chen, Eliesa Ing, Yali Jia, and David Huang. "Effect of algorithms and covariates in glaucoma diagnosis with optical coherence tomography angiography." British Journal of Ophthalmology 106, no. 12 (2022): 1703-1709.

2020

12. Qisheng You, Jie Wang, Yukun Guo, Shaohua Pi, Christina J. Flaxel, Steven T. Bailey, David Huang, Yali Jia, and Thomas S. Hwang. "Optical coherence tomography angiography avascular area association with 1-year treatment requirement and disease progression in diabetic retinopathy." American journal of ophthalmology 217 (2020): 268-277.

11. Shaohua Pi, Tristan T. Hormel, Xiang Wei, William Cepurna, Bingjie Wang, John C. Morrison, and Yali Jia. "Retinal capillary oximetry with visible light optical coherence tomography." Proceedings of the National Academy of Sciences 117, no. 21 (2020): 11658-11666.

First retinal capillary oximetry

Fig. 1 Representative capillary sO2 along with that in major vessels (A: artery, V: vein) in one rat retina responding to regulation in oxygen concentration in inhaled gas, from 21% (normoxia) to 15% (hypoxia), then to 100% (hyperoxia) and to 21% (return to normoxia). The angiogram (2×2-mm) was obtained by averaging all 8 scans at all conditions acquired in the same region. The sO2 in capillary segments corresponded to trends shown by the sO2 in major vessels, which decreased with the reduction of oxygen concentration in the inhaled gas.

Fig. 2 Ultra-wide-field angiogram of rat retinal vessels stitched from multiple scans with smaller field of view.

10. Shaohua Pi, Tristan T. Hormel, Xiang Wei, William Cepurna, John C. Morrison, and Yali Jia. "Imaging retinal structures at cellular-level resolution by visible-light optical coherence tomography." Optics letters 45, no. 7 (2020): 2107-2110.

In vivo cellular-resolution retinal imaging

2019

9. Shaohua Pi, Tristan T. Hormel, Xiang Wei, William Cepurna, Acner Camino, Yukun Guo, David Huang, John C. Morrison, and Yali Jia. "Monitoring retinal responses to acute intraocular pressure elevation in rats with visible light optical coherence tomography." Neurophotonics 6, no. 4 (2019): 041104.

The PI's first paper on animal model

Fig. 1 En face images (2.2 × 2.2 mm2) showing retinal vascular perfusion responses to acute IOP elevation

Comprehensive retinal responses to acute IOP elevation

which include retinal oxygen extraction and oxygen metabolism, as well as structural reflectivity, angiography and blood flow, all provided with vis-OCT simultaneously.

8. Bingjie Wang, Acner Camino, Shaohua Pi, Yukun Guo, Jie Wang, David Huang, Thomas S. Hwang, and Yali Jia. "Three-dimensional structural and angiographic evaluation of foveal ischemia in diabetic retinopathy: method and validation." Biomedical optics express 10, no. 7 (2019): 3522-3532.

7. Xiang Wei, Tristan T. Hormel, Shaohua Pi, Yukun Guo, Yifan Jian, and Yali Jia. "High dynamic range optical coherence tomography angiography (HDR-OCTA)." Biomedical optics express 10, no. 7 (2019): 3560-3571.

6. Xiang Wei, Acner Camino, Shaohua Pi, Tristan T. Hormel, William Cepurna, David Huang, John C. Morrison, and Yali Jia. "Real-time cross-sectional and en face OCT angiography guiding high-quality scan acquisition." Optics letters 44, no. 6 (2019): 1431-1434.

5. Shaohua Pi, Acner Camino, Xiang Wei, Tristan T. Hormel, William Cepurna, John C. Morrison, and Yali Jia. "Automated phase unwrapping in Doppler optical coherence tomography." Journal of biomedical optics 24, no. 1 (2019): 010502.

Invention of automated phase unwrapping algorithm

Fig. 2 Demonstration of phase unwrapping of a vein and an artery affected by phase wrapping, as well as a vein free of phase wrapping.

2018

4. Shaohua Pi, Acner Camino, Xiang Wei, Joseph Simonett, William Cepurna, David Huang, John C. Morrison, and Yali Jia. "Rodent retinal circulation organization and oxygen metabolism revealed by visible-light optical coherence tomography." Biomedical optics express 9, no. 11 (2018): 5851-5862.

The PI's first demonstration of retinal flow transition pattern in rats

Fig. 1 The 3D schematic vascular network illustrates the flow transition from artery to vein in rat retina with microvasculature architecture corresponding to the current findings.

Fig. 2 Retinal oxygen metabolic rate measurement with visible light OCT.

rTRO2: Retinal oxygen transport rate.

rMRO2: Retinal oxygen metabolic rate.

3. Xiang Wei, Acner Camino, Shaohua Pi, William Cepurna, David Huang, John C. Morrison, and Yali Jia. "Fast and robust standard-deviation-based method for bulk motion compensation in phase-based functional OCT." Optics letters 43, no. 9 (2018): 2204-2207.

2. Shaohua Pi, Acner Camino, William Cepurna, Xiang Wei, Miao Zhang, David Huang, John Morrison, and Yali Jia. "Automated spectroscopic retinal oximetry with visible-light optical coherence tomography." Biomedical optics express 9, no. 5 (2018): 2056-2067.

The PI's first OCT oximetry paper

Fig. 1 Logarithmic absorption extinction coefficients of oxygenated hemoglobin (HbO2) and deoxygenated hemoglobin (Hb) in the wavelength range from 400 nm to 1000 nm. The much higher extinction coefficients in the visible range (vis-OCT) compared to the infrared range (standard OCT) provides a better contrast to quantify oxygen saturation (sO2).

Oxygen Saturation

sO2 = CHbO2 / (CHbO2 + CHb)

Oxygen saturation is the fraction of oxygen-saturated hemoglobin relative to total hemoglobin in the blood. If quantified accurately, sO2 could be used as a biomarker to monitor retinal metabolism and provide a valuable early indicator of ocular disease.

Fig. 2 (a)-(c): Arteries demonstrate higher oxygen saturation (sO2) than veins by visible light OCT oximetry. Red: artery. Green: vein. The sO2 of each vessel is overlaid on structural en face images. (d)- (f): Fundus images. (g)- (i): Doppler OCT images around the optic disc show opposite flow directions between arteries and veins.

2017

1. Pi, Shaohua, Acner Camino, Miao Zhang, William Cepurna, Gangjun Liu, David Huang, John Morrison, and Yali Jia. "Angiographic and structural imaging using high axial resolution fiber-based visible-light OCT." Biomedical optics express 8, no. 10 (2017): 4595-4608.

The PI's first vis-OCT paper

Fig. 1 (A) Schematic of the visible light optical coherence tomography (vis-OCT) system for rat retina imaging. L1, L2: Lens. (B) Calibrated spectrum in spectrometer using a Neon calibration light source. The center wavelength is 560 nm and full maximum at half width (FWHM) bandwidth is 90 nm. (C) Maximum sensitivity was 89 dB considering the light passes a neutral density (ND) filter (OD = 3.0) twice. Inset shows the measured axial resolution 1.7 μm in air, which is equivalent to 1.2 μm in tissue.

Fig. 2 3.2 × 3.2-mm rat retinal en face angiograms of the (A) superficial vascular plexus (SVP), (B) intermediate capillary plexus (ICP), (C) deep capillary plexus (DCP), and (D) choriocapillaris (CC). scale bar = 200 μm.

Prior to OCT

Pi, Shaohua, Xie Zeng, Nan Zhang, Dengxin Ji, Borui Chen, Haomin Song, Alec Cheney et al. "Dielectric-grating-coupled surface plasmon resonance from the back side of the metal film for ultrasensitive sensing." IEEE Photonics Journal 8, no. 1 (2015): 1-7.

Nanophotonics

I designed a novel nano-structure which can launch surface plasmon resonance (SPR) modes efficiently from the back side of metal film, can excite the SPR under the normal incident light, demonstrated very narrow (~4 nm) resonance line width, and showed ultra-wide spectral tunability.

6) Wang, Bingjie, Shaohua Pi, Qi Sun, and Bo Jia. "Improved wavelet packet classification algorithm for vibrational intrusions in distributed fiber-optic monitoring systems." Optical Engineering 54, no. 5 (2015): 055104.

Machine Learning

I assisted to develop an intrusion classification algorithm based on wavelet packet transform, Shannon entropy and neural network.

Pi, Shaohua, Bingjie Wang, Bo Jia, Qi Sun, Qian Xiao, and Dong Zhao. "Intrusion localization algorithm based on linear spectrum in distributed Sagnac optical fiber sensing system." Optical Engineering 54, no. 8 (2015): 085105.

Optical Sensing

I developed a Sagnac-based optical fiber sensing system and a "twice-FFT" algorithm to detect and localize vibrational intrusions along a pipeline in real-time.

Zhao, Jiang, Shaohua Pi, Bingjie Wang, and Hongyan Wu. "Harmonic peak locations based on the twice fast Fourier transform algorithm in a Sagnac intrusion sensing system." Applied Optics 55, no. 10 (2016): 2675-2680.

Pi, Shaohua, Bingjie Wang, Jiang Zhao, and Qi Sun. "High-spatial-resolution localization algorithm based on cascade deconvolution in a distributed Sagnac interferometer invasion monitoring system." Applied Optics 55, no. 29 (2016): 8180-8184.

Wang, Bingjie, Shaohua Pi, Bo Jia, Qi Sun, and Dong Zhao. "Location performance fading for multiple disturbances in distributed Sagnac optical fiber interferometer." Microwave and Optical Technology Letters 57, no. 10 (2015): 2294-2298.

Pi, Shao Hua, Wang BingJie, Zhao Dong, and Jia Bo. "Multi-resolution intrusion localization algorithm through cepstrum in distributed fiber optic Sagnac interferometer." Acta Physica Sinica 65, no. 4 (2016).

Li, Honglei, Pi Shaohua, and Zhang Qun. "Exploring the stability of threshold voltage for W adopted IZO Thin Film Transistor (IZO: W TFT)." Fudan's Undergraduate Research Opportunities Program, (2010-2011)

Thin Film Transistor (TFT)

I fabricated the IZO: W TFT with magnetron sputtering at different oxygen partial pressure, and measured its electric and optical characterization with step profiler, SEM and spectrophotometer.

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