CMOS Time-Domain Imager for Functional Brain Imaging Using Gated Near-Infrared Spectroscopy
Notice bibliographique
Résumé
Non-invasive imaging of brain activity enables novel studies in neuroscience and provides an alternative modality for clinical monitoring applications. Near-infrared spectroscopic imaging (NIRSI) is non-invasive, cheap, portable, and immune to electro-magnetic interference. NIRSI is also superior in terms of spatial or temporal resolution when compared to electro-encephalography (EEG) or magnetic resonance imaging (MRI), respectively. Utilizing the time-domain (TD) technique offers the richest information at the cost of being the most complex[1]. TD NIRS imagers utilize time-correlated single-photon-counting (TCSPC) measurements which require detectors with single-photon sensitivity like single-photon avalanche diodes (SPADs)[2] or Silicon photomultipliers (SiPMs) and very fast time-discriminators like time-discriminator circuits (TDCs). Implementing these circuits in well-established and mature CMOS technologies[3] is advantageous. The main challenges in designing a TD NIRSI sensor deal with four issues: spectral responsivity, noise, fill-factor, and throughput. The spectral responsivity and noise are shaped by the technology process and structure (see figure 2) of the SPAD[4]. The fill-factor is determined by the ancillary circuitry needed to maintain the TD operation of the SPAD[4] (i.e., frontend, gating, and TDC). The throughput is dependent on the readout architecture of the array of pixels. We are proposing a fully integrated scalable array of time-gated actively-quenched SPADs with shared time-gated ring-oscillator-based TDCs following H-tree-based architecture and a 3-transistor active-pixel sensor (3T APS) readout scheme with in-pixel storage capability to be implemented using standard deep sub-micron CMOS technology. For example, using 130 nm CMOS technology SPADs can be built with an area of 50 um2 which exhibit a dark count rate (DCR) of 18 KHz[5]. At a wavelength around 600 nm and an excess bias of 2 V, their photon detection probability (PDP) could reach 22%. These SPADs breakdown at 20 V and could resolve down to 90 ps for wavelengths around 654 nm. With the same technology a 0.04 mm2 TDC can be designed with a resolution or least significant bit (LSB) of 6 ps for a range of 11-bits[6]. Moreover, SPAD structure variations, novel gating schemes, smart resource sharing, and efficient array architecture a CMOS TD NIRSI sensor can be realized to meet requirements of functional human brain imaging applications. References [1] A. Torricelli, D. Contini, A. Pifferi, M. Caffini, R. Re, L. Zucchelli and L. Spinelli, "Time domain functional NIRS imaging for human brain mapping," J NeuroImage, 2013. [2] E. Villella, O. Alonso, A. V. A. Montiel and A. Dieguez, "A low-noise time-gated single-photon detector in HV-CMOS technology for triggered imaging," Sensors and Actuators A: Physical, vol. 201, p. 342, 2013. [3] C. Niclass, M. Soga, H. Matsubara, M. Ogawa and M. Kagami, "A 0.18-um CMOS SoC for a 100-nm-Range 10-Frame/s 200 x 96-Pixel Time-of-Flight Depth Sensor," IEEE Journal of Solid-State Circuits, vol. 49, no. 1, 2014. [4] D. Palubiak, M. El-Desouki, O. Marinov, M. J. Deen and Q. Fang, "High-Speed, Single-Photon Avalanche-Photodiode Imager for Biomedical Applications," IEEE Sensors Journal, vol. 11, no. 10, p. 2401, 2011. [5] E. Webster, L. Grant and R. Henderson, "A High-Performance Single-Photon Avalanche Diode in 130-nm CMOS Imaging Technology," IEEE Electron Device Letters, vol. 33, no. 11, p. 1589, 2012. [6] M. Straayer and M. Perrott, "A multi-path gated ring oscillator TDC with first-order noise shaping," IEEE Journal of Solid-State Circuits, vol. 44, no. 4, p. 1089, 2009. [7] M. Ferrari and V. Quaresima, "A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application," J NeuroImage, vol. 63, p. 921, 2012. [8] L. Braga, L. Gasparini, L. Grant, R. Henderson, N. Massari, M. Perenzoni, D. Stoppa and R. Walker, "A Fully Digital 8 x 16 SiPM Array for PET Applications With Per-Pixel TDCs and Real-Time Energy Output," IEEE Journal of Solid-State Circuits, vol. 49, no. 1, 2014.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,006 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».