Technology, Research, & Development Project 3

Computational methods for quantitative analysis of in vivo fluorescence images

Aim 1: Implement algorithms to correct motion artifact, stitch frames, and perform 3D volume rendering

Aim 2: Generate deep learning methods to perform denoising, mitigate motion, and detect disease

Aim 3: Develop methods of spectral unmixing to perform lineage tracing of fluorescently labeled cells

Algorithmic methods

Conventional imaging processing strategies are provided to evaluate vertical sections collected using 3-axis scan mechanisms (TR&D1) installed in the distal end of flexible fiber-coupled microendoscopes (TR&D2) to accurately control the focus. This unique technology will enable fluorescence images to be collected in vivo from the epithelium in horizontal (XY) and vertical (XZ) planes, Image processing methods will be provided to perform 3D rendering to visualize interactions among of different cell populations to investigate biologic pheneomena in the tissue microenvironment over time.

Artificial intelligence

Deep learning methods will be provided to rapidly interpret in vivo fluorescence images collected. Computational tools using unsupervised networks will be developed to denoise the fluorescence images, mitigate motion artifact, and segment epithelial features, such as individual cells, crypt structures, and lamina propria. Machine learning models will be trained on existing image dataset to provide accurate disease detection, diagnosis, and risk stratification. These methods can be installed in portable imaging systems for real-time pre-clinical and clinical decision-making.

Spectral unmixing

Microendoscopes (TR&D2) have been adapted to collect multi-spectral fluorescence images to repetitively to track multiple cell populations in in vivo over time. The spatial relationships among different cell populations can be visualized and quantified in a dynamic manner. Image analysis pipelines have been integrated to accurately map cell lineage, study morphology and reveal network patterns with unprecedented speed and scale. The fate of individual cells within their innate tissue microenvironment determines how they specialize into different functional types.

Tissue microenvironment. Microendoscopes will be equipped with monolithic, 3-axis scanning mechanisms for use to collect fluorescence images in vivo from the epithelium in A) horizontal (XY) and B) vertical (XZ) planes. C) These images will be combined to generate 3D volumetric image. Image processing methods, including handcrafted and deep learning, will be used to visualize cell-cell interactions in the tissue microenvironment.

Publications

Letner JG, Patel PR, Hsieh JC, Smith Flores IM, Della Valle E, Walker LA, Weiland JD, Chestek CA, Cai D. Post-explant profiling of subcellular-scale carbon fiber intracortical electrodes and surrounding neurons enables modeling of recorded electrophysiology. J Neural Eng 2023;20:026019. PMC10022369.
Farzaneh N, Stein EB, Soroushmehr R, Gryak J, Najarian K. A deep learning framework for automated detection and quantitative assessment of liver trauma. BMC Med Imaging 2022;22:39. PMC8905785.
Minoccheri C, Williamson CA, Hemmila M, Ward K, Stein EB, Gryak J, Najarian K. An interpretable neural network for outcome prediction in traumatic brain injury. BMC Med Inform Decis Mak 2022;22:203. PMC9341077.
Walker LA, Williams JS, Li Y, Roossien DH, Lee WJ, Michki NS, Cai D. nGauge: Integrated and Extensible Neuron Morphology Analysis in Python. Neuroinformatics 2022; PMC9720862.
Kim RB, Alge OP, Liu G, Biesterveld BE, Wakam G, Williams AM, Mathis MR, Najarian K, Gryak J. Prediction of postoperative cardiac events in multiple surgical cohorts using a multimodal and integrative decision support system. Sci Rep 2022;12:11347. PMC9256604.
Yao H, Najarian K, Gryak J, Bishu S, Rice MD, Waljee AK, Wilkins HJ, Stidham RW. Fully automated endoscopic disease activity assessment in ulcerative colitis. Gastrointest Endosc 2021;93:728-736.e1. PMID: 32810479.
Li Y, Walker LA, Zhao Y, Edwards EM, Michki NS, Cheng HPJ, Ghazzi M, Chen TY, Chen M, Roossien DH, Cai D. Bitbow Enables Highly Efficient Neuronal Lineage Tracing and Morphology Reconstruction in Single Drosophila Brains. Front Neural Circuits 2021;15:732183. PMC8564373.
Iyer K, Najarian CP, Fattah AA, Arthurs CJ, Soroushmehr SMR, Subban V, Sankardas MA, Nadakuditi RR, Nallamothu BK, Figueroa CA. AngioNet: a convolutional neural network for vessel segmentation in X-ray angiography. Sci Rep 2021;11:18066. PMC8433338.
Kim RB, Gryak J, Mishra A, Cui C, Soroushmehr SMR, Najarian K, Wrobel JS. Utilization of smartphone and tablet camera photographs to predict healing of diabetes-related foot ulcers. Comput Biol Med 2020;126:104042. PMC9058995.
Shen FY, Harrington MM, Walker LA, Cheng HPJ, Boyden ES, Cai D. Light microscopy based approach for mapping connectivity with molecular specificity. Nature Communications 2020;11: 4632. PMC7493953.
Patel PR, Popov P, Caldwell CM, Welle E, Egert D, Pettibone JR, Roossien, DH, Becker, J, Berke, J, Chestek, CA#, Cai, D. High density carbon fiber arrays for chronic electrophysiology, fast scan cyclic voltammetry, and correlative anatomy. Journal of Neural Engineering 2020;17:056029. PMID: 33055366.
Egert D, Pettibone JR, Lemke S, Patel PR, Caldwell CM, Cai D, Ganguly K, Chestek CA, Berke J (2020) Cellular-scale silicon probes for high-density, precisely-localized neurophysiology. Journal of Neurophysiology 124:1578. PMC7814906.
Reamaroon N, Sjoding MW, Derksen H, Sabeti E, Gryak J, Barbaro RP, Athey BD, Najarian K. Robust segmentation of lung in chest x-ray: applications in analysis of acute respiratory distress syndrome. BMC Med Imaging 2020;20:116. PMC7566051.
Bianchi J, de Oliveira Ruellas AC, Gonçalves JR, Paniagua B, Prieto JC, Styner M, Li T, Zhu H, Sugai J, Giannobile W, Benavides E, Soki F, Yatabe M, Ashman L, Walker D, Soroushmehr R, Najarian K, Cevidanes LHS. Osteoarthritis of the Temporomandibular Joint can be diagnosed earlier using biomarkers and machine learning. Sci Rep 2020;10:8012. PMC7228972.
Shen FY, Harrington MM, Walker LA, Cheng HPJ, Boyden ES, Cai D (2020) Light microscopy based approach for mapping connectivity with molecular specificity. Nature Communications 11:4632. PMC7493953.
Yao H, Williamson C, Gryak J, Najarian K. Automated hematoma segmentation and outcome prediction for patients with traumatic brain injury. Artif Intell Med 2020;107:101910. PMID: 32828449.
Dizaji AS, Walker LA, Cai D (2020) TraceMontage: A method for merging multiple independent neuronal traces. J Neurosci Methods 332:108560. PMC6950642.
Roossien DH, Sadis BV, Yan Y, Webb JM, Min LY, Dizaji AS, Bogart LJ, Mazuski C, Huth RS, Stecher JS, Akula S, Shen F, Li Y, Xiao T, Vandenbrink M, Lichtman JW, Hensch TK, Herzog ED, Cai D. Multispectral tracing in densely labeled mouse brain with nTracer. Bioinformatics 2019;35:3544-46. PMC6748755.
Yao H, Stidham RW, Soroushmehr R, Gryak J, Najarian K. Automated Detection of Non-Informative Frames for Colonoscopy Through a Combination of Deep Learning and Feature Extraction. Annu Int Conf IEEE Eng Med Biol Soc 2019;2019:2402-2406. PMID: 31946383.
Veling MW, Li Y, Veling MT, Litts C, Michki N, Liu H, Ye B, Cai D. Identification of Neuronal Lineages in the Drosophila Peripheral Nervous System with a "Digital" Multi-spectral Lineage Tracing System. Cell Rep. 2019;29:3303-3312.e3. PMC6913890.

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