A Low-Power and Wide Dynamic Range Digital Pixel Sensor for Intrinsic Optical Imaging in Image-Guided Neurosurgery and Neocortical Epilepsy
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Abstract
Purpose: Determining the borders of brain tumors, seizure foci, and their elimination in patients with brain tumors is very important in preventing cancer recurrence. Multispectral Optical Intrinsic Signal Imaging (MS-OISI) image-guided neurosurgery using visible-Near-Infrared (NIR) wavelengths have shown great potential for image-guided neurosurgery. One of the main challenges is the need for low-power consumption, high-speed and above 100dB dynamic range to capture both visible and NIR photons. The overarching goal of this work is to create a Digital Pixel Sensor (DPS) as a Complementary Metal-Oxide-Semiconductor (CMOS) camera for MS-OISI of the brain in image-guided neurosurgery that has a wide dynamic range, low power consumption, and high speed.
Materials and Methods: The general view of neurosurgical system, DPS, and circuit operation of conventional Pulsed Frequency Modulation (PFM) DPS are given first. The proposed PFM DPS and circuit implementation are shown, as well as simulation results obtained using a circuit simulator. Finally, a comparison with other similar works is given.
Results: The proposed pixel simulation results show that the performance parameters such as dynamic range and power consumption has improved in comparison to similar works. However, due to its complicated circuitry, it has a low spatial resolution, which can be compensated.
Conclusion: The image sensor is post-layout simulated in 0.18μm CMOS technology with a 1.3V supply voltage, resulting in 140dB dynamic range and 7.69μW power dissipation with a 11% fill factor. The key novelty for the proposed PFM DPS is: in-pixel Analog-to-Digital Conversion (ADC), using a low voltage and high-speed dynamic comparator. Furthermore, this work uses a self-reset mechanism, which eliminates the need for an external pulse source, as well as variable reference voltage, which eliminates the necessity for a global constant reference voltage. All of these features demonstrate the excellent potential of the proposed pixel for MS-OISI image-guided neurosurgery.
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22- Sasagawa, Kiyotaka, et al. "An implantable CMOS image sensor with self-reset pixels for functional brain imaging. "IEEE Transactions on Electron Devices, 63.1: 215-222, (2015).
23- Sasagawa, Kiyotaka, et al. "Hemodynamic imaging using an implantable self-reset Image Sensor." IEEE Biomedical Circuits and Systems Conference(BioCAS)IEEE, (2016).
24- George, Swetha S., Mark F. Bocko, and Zeljko Ignjatovic. "Current sensing-assisted active pixel sensor for high-speed CMOS image sensors."IEEE Sensors Journal, 15.8: 4365-4372, (2015).
25- Cui, Nan. "Bio-Inspired Multi-Spectral Image Sensor and Augmented Reality Display for Near-Infrared Fluorescence Image-Guided Surgery.", Washington University in St. Louis, (2018).
26- Taverni, Gemma, et al. "In-vivo imaging of neural activity with dynamic vision sensors." IEEE Biomedical Circuits and Systems Conference(BioCAS). IEEE, (2017).
27- Shishido, Sanshiro, et al. "CMOS image sensor for recording of intrinsic-optical-signal of the brain." International SoC Design Conference(ISOCC).IEEE, (2009).
28- Guevara, E., et al. "Low-cost embedded system for optical imaging of intrinsic signals."Revista mexicana de fisica 65.6 (2019): 651-657.
29- Zhang, Xiao, et al. "CMOS image sensor and system for imaging hemodynamic changes in response to deep brain stimulation."IEEE Transactions on Biomedical Circuits and Systems 10.3: 632-642, (2015).
30- Haruta, Makito, et al. "Intrinsic signal imaging of brain function using a small implantable CMOS imaging device. "Japanese Journal of Applied Physics, 54.4S: 04DL10, (2015).
31- Yamaguchi, Takahiro, et al. "Implantable self-reset CMOS image sensor and its application to hemodynamic response detection in living mouse brain." Japanese Journal of Applied Physics, 55.4S: 04EM02, (2016).
32- Zhang, Xiao. "High-Performance CMOS Image Sensor and System for Imaging Tissue Hemodynamics." MS thesis. Graduate Studies, (2014).
33- Chen, Eric. "Low-noise image sensor designed for near-infrared image-guided surgery." (2019).
34- Hassanli, K., Sayedi, S. M., & Wikner, J. J. "A compact, low-power, and fast pulse-width modulation based digital pixel sensor with no bias circuit.", Sensors and Actuators A:Physical, 244, 243-251, (2016).
35- Park, Dongwon, Jehyuk Rhee, and Youngjoong Joo. "Wide dynamic range and high SNR self-reset CMOS image sensor using a Schmitt trigger."SENSORS, IEEE, (2008).
36- Hassanli, Kourosh, Sayed Masoud Sayedi, and J. Jacob Wikner. "High resolution digital imager based on time multiplexing algorithm." IEEE Sensors Journal 17.9: 2831-2840, (2017).
37-Hirsch, Stefan, et al. "Realization and opto-electronic characterization of linear self-reset pixel cells for a high dynamic CMOS image sensor."Advances in Radio Science, 17: 239-247, (2019).
38- Gao, Zhiyuan, Yiming Zhou, and Jiangtao Xu. "Multi-ramp reference voltage PWM imaging scheme with enhanced dynamic range and correlated double sampling.", Microelectronic journal, 69: 91-100, (2017).
39- Chen, Y., Yuan, F., & Khan, G. "A new wide dynamic range CMOS pulse frequency-modulation digital image sensor with in-pixel variable reference voltage.", In 2008 51st Midwest Symposium on Circuits and Systems(pp.129-132).IEEE, (2008).
40- Yung, Y. F. "Digital pixel sensor (DPS) array based on pulse width modulation (PWM) scheme (Doctoral dissertation)." (2004),
41- Mori, M., et al. "An APD-CMOS image sensor toward high sensitivity and wide dynamic range."2016 IEEE International Electron Devices Meeting(IEDM). IEEE, 2016.
42- Snaevarsdottir, F. "CMOS Image Sensor Design Methodology Applied to Optical Tomography and Neural Networks", (2018).
43- Ghormishi, M. H., & Karami, M. A. "Design and optimization of backside illuminated image sensor for epiretinal implants." Computers and Electrical Engineering,45,352-358, (2015).
44- Chen, Eric. "Low-noise image sensor designed for near-infrared image-guided surgery." (2019).
45- Blair, Steven, et al. "A 3.47 e− Read Noise, 81 dB Dynamic Range Backside-Illuminated Multispectral Imager for Near-Infrared Fluorescence Image-Guided Surgery." 2020 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, (2020).
46- Chen, Zhenyue, et al. "Single camera imaging system for color and near-infrared fluorescence image guided surgery." Biomedical optics express, 5.8: 2791-2797, (2014).
47- Clancy, Neil T., et al. "Surgical spectral imaging." Medical image analysis, 63: 101699, (2020).
48- Garcia, Missael, et al. "A 1280 by 720 by 3, 250 mW, 24 fps hexachromatic imager for near-infrared fluorescence image-guided surgery." 2018 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, (2018)
49- Garcia, Nimrod Missael. "Bio-Inspired Multi-Spectral and Polarization Imaging Sensors for Image-Guided Surgery." (2017).
50- Blair, Steven, et al. "A 120 dB, asynchronous, time-domain, multispectral imager for near-infrared fluorescence image-guided surgery.", IEEE Biomedical Circuits and Systems Conference (BioCAS)IEEE, (2018).
2- Jolesz, Ferenc A., ed. "Intraoperative imaging and image-guided therapy.", Springer Science & Business Media, (2014).
3- Kim, D. N., Chae, Y. S., & Kim, M. Y. "X-ray and optical stereo-based 3D sensor fusion system for image-guided neurosurgery.", International journal of computer assisted radiology and surgery, 11(4), 529-541, (2016).
4- Liu, Xin‐Rui, et al. "Neurosurgical brain tumor detection based on intraoperative optical intrinsic signal imaging technique: A case report of glioblastoma." Journal of biophotonics, 13.1: e201900200, (2020).
5- Song, Yinchen, et al. "Intraoperative optical mapping of epileptogenic cortices during non-ictal periods in pediatric patients.", NeuroImage:clinical, 11: 423-434, (2016).
6- Schwartz, Theodore H. "The application of optical recording of intrinsic signals to simultaneously acquire functional, pathological and localizing information and its potential role in neurosurgery.", Stereotactic and functional neurosurgery, 83.1: 36-44, (2005).
7- Song, Yinchen, et al. "Intraoperative optical mapping of epileptogenic cortices during non-ictal periods in pediatric patients.", NeuroImage:Clinical, 11: 423-434, (2016).
8- Choi, Christopher, et al. "Localizing seizure activity in the brain using implantable micro‐LEDs with quantum dot downconversion.", Advanced Materials Technologies 3.6: 1700366, (2018).
9- Sigal, Iliya, et al. "Imaging brain activity during seizures in freely behaving rats using a miniature multi-modal imaging system.", Biomedical optics express7.9: 3596-3609, (2016).
10- Chance, B., et al. "Optical imaging of brain function and metabolism."Journal of neurology, 239.7:359-360, (1992).
11- Liang, Rongguang. "Optical design for biomedical imaging." SPIE, (2011).
12- Toga, Arthur W., and John C. Mazziotta.Brain mapping: the methods.Academic press, (2002).
13- Srilahari, N., et al. "Non-Invasive Functional Optical Brain Imaging Methods: A Review.", International Journal of Research and Review, Vol.7; Issue: 5; (2020).
14- Sen, A. N., Gopinath, S. P., & Robertson, C. S. "Clinical application of near-infrared spectroscopy in patients with traumatic brain injury: a review of the progress of the field. ", Neurophotonics, 3(3), 031409, (2016)
15- Nakajima, Arata, et al. "CMOS image sensor integrated with micro-LED and multielectrode arrays for the patterned photostimulation and multichannel recording of neuronal tissue."Optic express, 20.6: 6097-6108, (2012).
16- Morone, Katherine A., et al. "Review of functional and clinical relevance of intrinsic signal optical imaging in human brain mapping." Neurophotonics, 4.3: 031220, (2017).
17- Bahar, Sonya, et al. "In vivo intrinsic optical signal imaging of neocortical epilepsy."Bioimaging in neurodegeneration. Humana Press, 149-175, (2005).
18- Cui, Nan, et al. "A 110× 64 150 mW 28 frames/s integrated visible/near-infrared CMOS image sensor with dual exposure times for image guided surgery." IEEE International Symposium on Circuits and Systems(ISCAS). IEEE, (2016).
19- Zhao, Mingrui, et al. "Multi-spectral imaging of blood volume, metabolism, oximetry, and light scattering. "Neurovascular Coupling Methods . Humana Press, New York, NY, 201-219, (2014).
20- Bahar, Sonya, et al. "Intrinsic optical signal imaging of neocortical seizures: the ‘epileptic dip’."Neuroreport 17.5: 499-503, (2006).
21- Fossum, Eric R. "CMOS image sensors: Electronic camera-on-a-chip."IEE transactions on electron devices, 44.10: 1689-1698, (1997).
22- Sasagawa, Kiyotaka, et al. "An implantable CMOS image sensor with self-reset pixels for functional brain imaging. "IEEE Transactions on Electron Devices, 63.1: 215-222, (2015).
23- Sasagawa, Kiyotaka, et al. "Hemodynamic imaging using an implantable self-reset Image Sensor." IEEE Biomedical Circuits and Systems Conference(BioCAS)IEEE, (2016).
24- George, Swetha S., Mark F. Bocko, and Zeljko Ignjatovic. "Current sensing-assisted active pixel sensor for high-speed CMOS image sensors."IEEE Sensors Journal, 15.8: 4365-4372, (2015).
25- Cui, Nan. "Bio-Inspired Multi-Spectral Image Sensor and Augmented Reality Display for Near-Infrared Fluorescence Image-Guided Surgery.", Washington University in St. Louis, (2018).
26- Taverni, Gemma, et al. "In-vivo imaging of neural activity with dynamic vision sensors." IEEE Biomedical Circuits and Systems Conference(BioCAS). IEEE, (2017).
27- Shishido, Sanshiro, et al. "CMOS image sensor for recording of intrinsic-optical-signal of the brain." International SoC Design Conference(ISOCC).IEEE, (2009).
28- Guevara, E., et al. "Low-cost embedded system for optical imaging of intrinsic signals."Revista mexicana de fisica 65.6 (2019): 651-657.
29- Zhang, Xiao, et al. "CMOS image sensor and system for imaging hemodynamic changes in response to deep brain stimulation."IEEE Transactions on Biomedical Circuits and Systems 10.3: 632-642, (2015).
30- Haruta, Makito, et al. "Intrinsic signal imaging of brain function using a small implantable CMOS imaging device. "Japanese Journal of Applied Physics, 54.4S: 04DL10, (2015).
31- Yamaguchi, Takahiro, et al. "Implantable self-reset CMOS image sensor and its application to hemodynamic response detection in living mouse brain." Japanese Journal of Applied Physics, 55.4S: 04EM02, (2016).
32- Zhang, Xiao. "High-Performance CMOS Image Sensor and System for Imaging Tissue Hemodynamics." MS thesis. Graduate Studies, (2014).
33- Chen, Eric. "Low-noise image sensor designed for near-infrared image-guided surgery." (2019).
34- Hassanli, K., Sayedi, S. M., & Wikner, J. J. "A compact, low-power, and fast pulse-width modulation based digital pixel sensor with no bias circuit.", Sensors and Actuators A:Physical, 244, 243-251, (2016).
35- Park, Dongwon, Jehyuk Rhee, and Youngjoong Joo. "Wide dynamic range and high SNR self-reset CMOS image sensor using a Schmitt trigger."SENSORS, IEEE, (2008).
36- Hassanli, Kourosh, Sayed Masoud Sayedi, and J. Jacob Wikner. "High resolution digital imager based on time multiplexing algorithm." IEEE Sensors Journal 17.9: 2831-2840, (2017).
37-Hirsch, Stefan, et al. "Realization and opto-electronic characterization of linear self-reset pixel cells for a high dynamic CMOS image sensor."Advances in Radio Science, 17: 239-247, (2019).
38- Gao, Zhiyuan, Yiming Zhou, and Jiangtao Xu. "Multi-ramp reference voltage PWM imaging scheme with enhanced dynamic range and correlated double sampling.", Microelectronic journal, 69: 91-100, (2017).
39- Chen, Y., Yuan, F., & Khan, G. "A new wide dynamic range CMOS pulse frequency-modulation digital image sensor with in-pixel variable reference voltage.", In 2008 51st Midwest Symposium on Circuits and Systems(pp.129-132).IEEE, (2008).
40- Yung, Y. F. "Digital pixel sensor (DPS) array based on pulse width modulation (PWM) scheme (Doctoral dissertation)." (2004),
41- Mori, M., et al. "An APD-CMOS image sensor toward high sensitivity and wide dynamic range."2016 IEEE International Electron Devices Meeting(IEDM). IEEE, 2016.
42- Snaevarsdottir, F. "CMOS Image Sensor Design Methodology Applied to Optical Tomography and Neural Networks", (2018).
43- Ghormishi, M. H., & Karami, M. A. "Design and optimization of backside illuminated image sensor for epiretinal implants." Computers and Electrical Engineering,45,352-358, (2015).
44- Chen, Eric. "Low-noise image sensor designed for near-infrared image-guided surgery." (2019).
45- Blair, Steven, et al. "A 3.47 e− Read Noise, 81 dB Dynamic Range Backside-Illuminated Multispectral Imager for Near-Infrared Fluorescence Image-Guided Surgery." 2020 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, (2020).
46- Chen, Zhenyue, et al. "Single camera imaging system for color and near-infrared fluorescence image guided surgery." Biomedical optics express, 5.8: 2791-2797, (2014).
47- Clancy, Neil T., et al. "Surgical spectral imaging." Medical image analysis, 63: 101699, (2020).
48- Garcia, Missael, et al. "A 1280 by 720 by 3, 250 mW, 24 fps hexachromatic imager for near-infrared fluorescence image-guided surgery." 2018 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, (2018)
49- Garcia, Nimrod Missael. "Bio-Inspired Multi-Spectral and Polarization Imaging Sensors for Image-Guided Surgery." (2017).
50- Blair, Steven, et al. "A 120 dB, asynchronous, time-domain, multispectral imager for near-infrared fluorescence image-guided surgery.", IEEE Biomedical Circuits and Systems Conference (BioCAS)IEEE, (2018).
| Files | ||
| Issue | Vol 9 No 4 (2022) | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/fbt.v9i4.10383 | |
| Keywords | ||
| Dynamic Range Complementary Metal-Oxide-Semiconductor Pulsed Frequency Modulation Digital Pixel Sensor Image-Guided Neurosurgery Multispectral Optical Intrinsic Signal Imaging | ||
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How to Cite
1.
Salehifar Y, Ayatollahi A, Karami MA, Pirghayesh Ghurshagh M. A Low-Power and Wide Dynamic Range Digital Pixel Sensor for Intrinsic Optical Imaging in Image-Guided Neurosurgery and Neocortical Epilepsy. Frontiers Biomed Technol. 2022;9(4):255-264.
