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15,770 results on '"Robinson, A. L."'

1. MIBiG 4.0: advancing biosynthetic gene cluster curation through global collaboration

Author

Zdouc, Mitja M, Blin, Kai, Louwen, Nico LL, Navarro, Jorge, Loureiro, Catarina, Bader, Chantal D, Bailey, Constance B, Barra, Lena, Booth, Thomas J, Bozhüyük, Kenan AJ, Cediel-Becerra, José DD, Charlop-Powers, Zachary, Chevrette, Marc G, Chooi, Yit Heng, D’Agostino, Paul M, de Rond, Tristan, Del Pup, Elena, Duncan, Katherine R, Gu, Wenjia, Hanif, Novriyandi, Helfrich, Eric JN, Jenner, Matthew, Katsuyama, Yohei, Korenskaia, Aleksandra, Krug, Daniel, Libis, Vincent, Lund, George A, Mantri, Shrikant, Morgan, Kalindi D, Owen, Charlotte, Phan, Chin-Soon, Philmus, Benjamin, Reitz, Zachary L, Robinson, Serina L, Singh, Kumar Saurabh, Teufel, Robin, Tong, Yaojun, Tugizimana, Fidele, Ulanova, Dana, Winter, Jaclyn M, Aguilar, César, Akiyama, Daniel Y, Al-Salihi, Suhad AA, Alanjary, Mohammad, Alberti, Fabrizio, Aleti, Gajender, Alharthi, Shumukh A, Rojo, Mariela Y Arias, Arishi, Amr A, Augustijn, Hannah E, Avalon, Nicole E, Avelar-Rivas, J Abraham, Axt, Kyle K, Barbieri, Hellen B, Barbosa, Julio Cesar J, Segato, Lucas Gabriel Barboza, Barrett, Susanna E, Baunach, Martin, Beemelmanns, Christine, Beqaj, Dardan, Berger, Tim, Bernaldo-Agüero, Jordan, Bettenbühl, Sandra M, Bielinski, Vincent A, Biermann, Friederike, Borges, Ricardo M, Borriss, Rainer, Breitenbach, Milena, Bretscher, Kevin M, Brigham, Michael W, Buedenbender, Larissa, Bulcock, Brodie W, Cano-Prieto, Carolina, Capela, João, Carrion, Victor J, Carter, Riley S, Castelo-Branco, Raquel, Castro-Falcón, Gabriel, Chagas, Fernanda O, Charria-Girón, Esteban, Chaudhri, Ayesha Ahmed, Chaudhry, Vasvi, Choi, Hyukjae, Choi, Yukyung, Choupannejad, Roya, Chromy, Jakub, Donahey, Melinda S Chue, Collemare, Jérôme, Connolly, Jack A, Creamer, Kaitlin E, Crüsemann, Max, Cruz, Andres Arredondo, Cumsille, Andres, Dallery, Jean-Felix, Damas-Ramos, Luis Caleb, Damiani, Tito, de Kruijff, Martinus, Martín, Belén Delgado, Della Sala, Gerardo, and Dillen, Jelle

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Generic health relevance, Multigene Family, Databases, Genetic, Biosynthetic Pathways, Molecular Sequence Annotation, Biological Products, Data Curation, Environmental Sciences, Information and Computing Sciences, Developmental Biology, Biological sciences, Chemical sciences, Environmental sciences
Abstract

Specialized or secondary metabolites are small molecules of biological origin, often showing potent biological activities with applications in agriculture, engineering and medicine. Usually, the biosynthesis of these natural products is governed by sets of co-regulated and physically clustered genes known as biosynthetic gene clusters (BGCs). To share information about BGCs in a standardized and machine-readable way, the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard and repository was initiated in 2015. Since its conception, MIBiG has been regularly updated to expand data coverage and remain up to date with innovations in natural product research. Here, we describe MIBiG version 4.0, an extensive update to the data repository and the underlying data standard. In a massive community annotation effort, 267 contributors performed 8304 edits, creating 557 new entries and modifying 590 existing entries, resulting in a new total of 3059 curated entries in MIBiG. Particular attention was paid to ensuring high data quality, with automated data validation using a newly developed custom submission portal prototype, paired with a novel peer-reviewing model. MIBiG 4.0 also takes steps towards a rolling release model and a broader involvement of the scientific community. MIBiG 4.0 is accessible online at https://mibig.secondarymetabolites.org/.

Published
2025

2. Wetting-Layer-Assisted Synthesis of Inverted CdSe/PbSe Quantum Dots and their Photophysical and Photo-Electrical Properties

Author

Sayevich, Vladimir, Kim, Whi Dong, Robinson, Zachary L., Kozlov, Oleg V., Livache, Clément, Ahn, Namyoung, Jung, Heeyoung, and Klimov, Victor I.

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science
Abstract

Heterostructured quantum dots (QDs) based on narrow-gap PbSe and wide-gap CdSe have been studied with an eye on their prospective applications in near-infrared (NIR) light sources, photodetectors, and solar cells. The most common structural motif is a spherical QD comprising a PbSe core enclosed into a CdSe shell. However, the potential barrier created by the CdSe shell complicates extraction of band-edge charge carriers from the QD. Therefore, conventional PbSe/CdSe QDs are not suitable for applications in practical photoconversion devices. Here we report inverted CdSe/PbSe core/shell QDs that overcome this drawback. In these structures, both photocarriers (electron and hole) exhibit a significant degree of shell localization and are therefore free to move within the QD solid and be extracted into an external circuit. To create such QDs, we employ a novel synthetic method in which a thin, atomically controlled wetting layer is used to homogenize the surface of the CdSe core and thus promote directionally uniform growth of the PbSe shell. Unlike noninverted QDs, inverted core/shell structures exhibit highly efficient photocarrier transport, making them excellent candidates for applications in practical photoconversion including photovoltaics, photodetection, and photochemistry., Comment: Total 39 pages, including main text, supporting information (SI), 5 main figures and 6 SI figures

Published
2024

5. Links Between Optical and X-ray Light in Cygnus X-2

Author

Igl, Alexander B., Hynes, R. I., O'Brien, K. S., Robinson, E. L., and Britt, C. T.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

We observed the low mass X-ray binary Cyg X-2 for a total of 18 nights over two observing runs in July and September of 2006, using the Otto Struve Telescope at McDonald Observatory and the Rossi X-ray Timing Explorer. Using discrete cross correlations, we found peaks occurring at near-zero lags in the flaring branch of the colour-colour diagram, which could signify reprocessing, in addition to an anti-correlation within the normal branch. When comparing optical flux to the system's placement on the Z track, two distinct behaviors were seen: (1) a state with no correlation, and (2) a multi-valued (horizontal and normal branches)/correlated (flaring branch) state. The correlation was the result of direct steps and more gradual falls to and from the flaring branch respectively. Finally, we modeled timed spectra with 64 second bins with an extended accretion disc corona model. We found that correlations occurred between the optical and the various fitted parameters, particularly the blackbody normalization (and blackbody radius by extension) in higher intensity regions. Despite this, the Z track location was found to be a far better predictor of physical parameters than the optical flux, with clean correlations seen in every branch of the Z track. Where optical correlations are found, the location on the Z track was a better predictor of optical flux than any individual physical parameter., Comment: 19 pages, MNRAS in press

Published
2024
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6. Ovarian tumor cells gain competitive advantage by actively reducing the cellular fitness of microenvironment cells

Author

Madan, Esha, Palma, António M., Vudatha, Vignesh, Kumar, Amit, Bhoopathi, Praveen, Wilhelm, Jochen, Bernas, Tytus, Martin, Patrick C., Bilolikar, Gaurav, Gogna, Aenya, Peixoto, Maria Leonor, Dreier, Isabelle, Araujo, Thais Fenz, Garre, Elena, Gustafsson, Anna, Dorayappan, Kalpana Deepa Priya, Mamidi, Narsimha, Sun, Zhaoyu, Yekelchyk, Michail, Accardi, Davide, Olsen, Amalie Lykke, Lin, Lin, Titelman, Asaf Ashkenazy, Bianchi, Michael, Jessmon, Phil, Farid, Elnaz Abbasi, Pradhan, Anjan K., Neufeld, Lena, Yeini, Eilam, Maji, Santanu, Pelham, Christopher J., Kim, Hyobin, Oh, Daniel, Rolfsnes, Hans Olav, Marques, Rita C., Lu, Amy, Nagane, Masaki, Chaudhary, Sahil, Gupta, Kartik, Gogna, Keshav C., Bigio, Ana, Bhoopathi, Karthikeya, Mannangatti, Padmanabhan, Achary, K. Gopinath, Akhtar, Javed, Belião, Sara, Das, Swadesh, Correia, Isabel, da Silva, Cláudia L., Fialho, Arsénio M., Poellmann, Michael J., Javius-Jones, Kaila, Hawkridge, Adam M., Pal, Sanya, Shree, Kumari S., Rakha, Emad A., Khurana, Sambhav, Xiao, Gaoping, Zhang, Dongyu, Rijal, Arjun, Lyons, Charles, Grossman, Steven R., Turner, David P., Pillappa, Raghavendra, Prakash, Karanvir, Gupta, Gaurav, Robinson, Gary L. W. G., Koblinski, Jennifer, Wang, Hongjun, Singh, Gita, Singh, Sujay, Rayamajhi, Sagar, Bacolod, Manny D., Richards, Hope, Sayeed, Sadia, Klein, Katherine P., Chelmow, David, Satchi-Fainaro, Ronit, Selvendiran, Karuppaiyah, Connolly, Denise, Thorsen, Frits Alan, Bjerkvig, Rolf, Nephew, Kenneth P., Idowu, Michael O., Kühnel, Mark P., Moskaluk, Christopher, Hong, Seungpyo, Redmond, William L., Landberg, Göran, Lopez-Beltran, Antonio, Poklepovic, Andrew S., Sanyal, Arun, Fisher, Paul B., Church, George M., Menon, Usha, Drapkin, Ronny, Godwin, Andrew K., Luo, Yonglun, Ackermann, Maximilian, Tzankov, Alexandar, Mertz, Kirsten D., Jonigk, Danny, Tsung, Allan, Sidransky, David, Trevino, Jose, Saavedra, Arturo P., Winn, Robert, Won, Kyoung Jae, Moreno, Eduardo, and Gogna, Rajan

Published
2024
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14. Diabetic Neuropathy: A Guide to Pain Management

Author

Zhang, Emily X., Yazdi, Cyrus, Islam, Rahib K., Anwar, Ahmed I., Alvares-Amado, Alana, Townsend, Horace, Allen, Kaitlyn E., Plakotaris, Elena, Hirsch, Jon D., Rieger, Ross G., Allampalli, Varsha, Hasoon, Jamal, Islam, Kazi N., Shekoohi, Sahar, Kaye, Alan D., and Robinson, Christopher L.

Published
2024
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24. Modeling Biphasic, Non-Sigmoidal Dose-Response Relationships: Comparison of Brain-Cousens and Cedergreen Models for a Biochemical Dataset

Author

Abbaraju, Venkat D., Robinson, Tamaraty L., and Weiser, Brian P.

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Biphasic, non-sigmoidal dose-response relationships are frequently observed in biochemistry and pharmacology, but they are not always analyzed with appropriate statistical methods. Here, we examine curve fitting methods for "hormetic" dose-response relationships where low and high doses of an effector produce opposite responses. We provide the full dataset used for modeling, and we provide the code for analyzing the dataset in SAS using two established mathematical models of hormesis, the Brain-Cousens model and the Cedergreen model. We show how to obtain and interpret curve parameters such as the ED50 that arise from modeling, and we discuss how curve parameters might change in a predictable manner when the conditions of the dose-response assay are altered. In addition to modeling the raw dataset that we provide, we also model the dataset after applying common normalization techniques, and we indicate how this affects the parameters that are associated with the fit curves. The Brain-Cousens and Cedergreen models that we used for curve fitting were similarly effective at capturing quantitative information about the biphasic dose-response relationships.

Published
2023

28. Association of quantitative histopathology measurements with antemortem medial temporal lobe cortical thickness in the Alzheimer’s disease continuum

Author

Denning, Amanda E., Ittyerah, Ranjit, Levorse, Lisa M., Sadeghpour, Niyousha, Athalye, Chinmayee, Chung, Eunice, Ravikumar, Sadhana, Dong, Mengjin, Duong, Michael Tran, Li, Yue, Ilesanmi, Ademola, Sreepada, Lasya P., Sabatini, Philip, Lowe, MaKayla, Bahena, Alejandra, Zablah, Jamila, Spencer, Barbara E., Watanabe, Ryohei, Kim, Boram, Sørensen, Maja Højvang, Khandelwal, Pulkit, Brown, Christopher, Hrybouski, Stanislau, Xie, Sharon X., de Flores, Robin, Robinson, John L., Schuck, Theresa, Ohm, Daniel T., Arezoumandan, Sanaz, Porta, Sílvia, Detre, John A., Insausti, Ricardo, Wisse, Laura E. M., Das, Sandhitsu R., Irwin, David J., Lee, Edward B., Wolk, David A., and Yushkevich, Paul A.

Published
2024
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31. Postmortem imaging reveals patterns of medial temporal lobe vulnerability to tau pathology in Alzheimer’s disease

Author

Ravikumar, Sadhana, Denning, Amanda E., Lim, Sydney, Chung, Eunice, Sadeghpour, Niyousha, Ittyerah, Ranjit, Wisse, Laura E. M., Das, Sandhitsu R., Xie, Long, Robinson, John L., Schuck, Theresa, Lee, Edward B., Detre, John A., Tisdall, M. Dylan, Prabhakaran, Karthik, Mizsei, Gabor, de Onzono Martin, Maria Mercedes Iñiguez, Arroyo Jiménez, Maria del Mar, Mũnoz, Monica, Marcos Rabal, Maria del Pilar, Cebada Sánchez, Sandra, Delgado González, José Carlos, de la Rosa Prieto, Carlos, Irwin, David J., Wolk, David A., Insausti, Ricardo, and Yushkevich, Paul A.

Published
2024
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34. Cardiometabolic Effects of Omnivorous vs Vegan Diets in Identical Twins

Author

Landry, Matthew J, Ward, Catherine P, Cunanan, Kristen M, Durand, Lindsay R, Perelman, Dalia, Robinson, Jennifer L, Hennings, Tayler, Koh, Linda, Dant, Christopher, Zeitlin, Amanda, Ebel, Emily R, Sonnenburg, Erica D, Sonnenburg, Justin L, and Gardner, Christopher D

Subjects
Public Health, Biomedical and Clinical Sciences, Nutrition and Dietetics, Health Sciences, Nutrition, Clinical Research, Complementary and Integrative Health, Cardiovascular, Prevention, Clinical Trials and Supportive Activities, Obesity, Prevention of disease and conditions, and promotion of well-being, 3.3 Nutrition and chemoprevention, Metabolic and endocrine, Adult, Female, Humans, Male, Body Weight, Cardiovascular Diseases, Cholesterol, LDL, Diet, Vegan, Insulins, Twins, Monozygotic, Vegetables, Middle Aged, Diet, Healthy, Biomedical and clinical sciences, Health sciences
Abstract

ImportanceIncreasing evidence suggests that, compared with an omnivorous diet, a vegan diet confers potential cardiovascular benefits from improved diet quality (ie, higher consumption of vegetables, legumes, fruits, whole grains, nuts, and seeds).ObjectiveTo compare the effects of a healthy vegan vs healthy omnivorous diet on cardiometabolic measures during an 8-week intervention.Design, setting, and participantsThis single-center, population-based randomized clinical trial of 22 pairs of twins (N = 44) randomized participants to a vegan or omnivorous diet (1 twin per diet). Participant enrollment began March 28, 2022, and continued through May 5, 2022. The date of final follow-up data collection was July 20, 2022. This 8-week, open-label, parallel, dietary randomized clinical trial compared the health impact of a vegan diet vs an omnivorous diet in identical twins. Primary analysis included all available data.InterventionTwin pairs were randomized to follow a healthy vegan diet or a healthy omnivorous diet for 8 weeks. Diet-specific meals were provided via a meal delivery service from baseline through week 4, and from weeks 5 to 8 participants prepared their own diet-appropriate meals and snacks.Main outcomes and measuresThe primary outcome was difference in low-density lipoprotein cholesterol concentration from baseline to end point (week 8). Secondary outcome measures were changes in cardiometabolic factors (plasma lipids, glucose, and insulin levels and serum trimethylamine N-oxide level), plasma vitamin B12 level, and body weight. Exploratory measures were adherence to study diets, ease or difficulty in following the diets, participant energy levels, and sense of well-being.ResultsA total of 22 pairs (N = 44) of twins (34 [77.3%] female; mean [SD] age, 39.6 [12.7] years; mean [SD] body mass index, 25.9 [4.7]) were enrolled in the study. After 8 weeks, compared with twins randomized to an omnivorous diet, the twins randomized to the vegan diet experienced significant mean (SD) decreases in low-density lipoprotein cholesterol concentration (-13.9 [5.8] mg/dL; 95% CI, -25.3 to -2.4 mg/dL), fasting insulin level (-2.9 [1.3] μIU/mL; 95% CI, -5.3 to -0.4 μIU/mL), and body weight (-1.9 [0.7] kg; 95% CI, -3.3 to -0.6 kg).Conclusions and relevanceIn this randomized clinical trial of the cardiometabolic effects of omnivorous vs vegan diets in identical twins, the healthy vegan diet led to improved cardiometabolic outcomes compared with a healthy omnivorous diet. Clinicians can consider this dietary approach as a healthy alternative for their patients.Trial registrationClinicalTrials.gov Identifier: NCT05297825.

Published
2023

35. Generative Adversarial Networks for Scintillation Signal Simulation in EXO-200

Author

Li, S., Ostrovskiy, I., Li, Z., Yang, L., Kharusi, S. Al, Anton, G., Badhrees, I., Barbeau, P. S., Beck, D., Belov, V., Bhatta, T., Breidenbach, M., Brunner, T., Cao, G. F., Cen, W. R., Chambers, C., Cleveland, B., Coon, M., Craycraft, A., Daniels, T., Darroch, L., Daugherty, S. J., Davis, J., Delaquis, S., Der Mesrobian-Kabakian, A., DeVoe, R., Dilling, J., Dolgolenko, A., Dolinski, M. J., Echevers, J., Fairbank Jr., W., Fairbank, D., Farine, J., Feyzbakhsh, S., Fierlinger, P., Fu, Y. S., Fudenberg, D., Gautam, P., Gornea, R., Gratta, G., Hall, C., Hansen, E. V., Hoessl, J., Hufschmidt, P., Hughes, M., Iverson, A., Jamil, A., Jessiman, C., Jewell, M. J., Johnson, A., Karelin, A., Kaufman, L. J., Koffas, T., Krücken, R., Kuchenkov, A., Kumar, K. S., Lan, Y., Larson, A., Lenardo, B. G., Leonard, D. S., Li, G. S., Licciardi, C., Lin, Y. H., MacLellan, R., McElroy, T., Michel, T., Mong, B., Moore, D. C., Murray, K., Njoya, O., Nusair, O., Odian, A., Perna, A., Piepke, A., Pocar, A., Retière, F., Robinson, A. L., Rowson, P. C., Runge, J., Schmidt, S., Sinclair, D., Skarpaas, K., Soma, A. K., Stekhanov, V., Tarka, M., Thibado, S., Todd, J., Tolba, T., Totev, T. I., and Tsang, R.

Subjects
High Energy Physics - Experiment, Computer Science - Machine Learning, Physics - Instrumentation and Detectors
Abstract

Generative Adversarial Networks trained on samples of simulated or actual events have been proposed as a way of generating large simulated datasets at a reduced computational cost. In this work, a novel approach to perform the simulation of photodetector signals from the time projection chamber of the EXO-200 experiment is demonstrated. The method is based on a Wasserstein Generative Adversarial Network - a deep learning technique allowing for implicit non-parametric estimation of the population distribution for a given set of objects. Our network is trained on real calibration data using raw scintillation waveforms as input. We find that it is able to produce high-quality simulated waveforms an order of magnitude faster than the traditional simulation approach and, importantly, generalize from the training sample and discern salient high-level features of the data. In particular, the network correctly deduces position dependency of scintillation light response in the detector and correctly recognizes dead photodetector channels. The network output is then integrated into the EXO-200 analysis framework to show that the standard EXO-200 reconstruction routine processes the simulated waveforms to produce energy distributions comparable to that of real waveforms. Finally, the remaining discrepancies and potential ways to improve the approach further are highlighted., Comment: As accepted by JINST

Published
2023
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36. Search for Two-neutrino Double-Beta Decay of $^{136}\rm Xe$ to the $0^+_1$ excited state of $^{136}\rm Ba$ with the Complete EXO-200 Dataset

Author

Collaboration, EXO-200, Kharusi, S. Al, Anton, G., Badhrees, I., Barbeau, P. S., Beck, D., Belov, V., Bhatta, T., Breidenbach, M., Brunner, T., Cao, G. F., Cen, W. R., Chambers, C., Cleveland, B., Coon, M., Craycraft, A., Daniels, T., Darroch, L., Daugherty, S. J., Davis, J., Delaquis, S., Der Mesrobian-Kabakian, A., DeVoe, R., Dilling, J., Dolgolenko, A., Dolinski, M. J., Echevers, J., Fairbank Jr., W., Fairbank, D., Farine, J., Feyzbakhsh, S., Fierlinger, P., Fu, Y. S., Fudenberg, D., Gautam, P., Gornea, R., Gratta, G., Hall, C., Hansen, E. V., Hoessl, J., Hufschmidt, P., Hughes, M., Iverson, A., Jamil, A., Jessiman, C., Jewell, M. J., Johnson, A., Karelin, A., Kaufman, L. J., Koffas, T., Krücken, R., Kuchenkov, A., Kumar, K. S., Lan, Y., Larson, A., Lenardo, B. G., Leonard, D. S., Li, G. S., Li, S., Li, Z., Licciardi, C., Lin, Y. H., MacLellan, R., McElroy, T., Michel, T., Mong, B., Moore, D. C., Murray, K., Njoya, O., Nusair, O., Odian, A., Ostrovskiy, I., Perna, A., Piepke, A., Pocar, A., Retière, F., Robinson, A. L., Rowson, P. C., Runge, J., Schmidt, S., Sinclair, D., Skarpaas, K., Soma, A. K., Stekhanov, V., Tarka, M., Thibado, S., Todd, J., Tolba, T., Totev, T. I., Tsang, R., Veenstra, B., Veeraraghavan, V., Vogel, P., Vuilleumier, J. -L., Wagenpfeil, M., Watkins, J., Weber, M., Wen, L. J., Wichoski, U., Wrede, G., Wu, S. X., Xia, Q., Yahne, D. R., Yang, L., Yen, Y. -R., Zeldovich, O. Ya., and Ziegler, T.

Subjects
High Energy Physics - Experiment, Nuclear Experiment
Abstract

A new search for two-neutrino double-beta ($2\nu\beta\beta$) decay of $^{136}\rm Xe$ to the $0^+_1$ excited state of $^{136}\rm Ba$ is performed with the full EXO-200 dataset. A deep learning-based convolutional neural network is used to discriminate signal from background events. Signal detection efficiency is increased relative to previous searches by EXO-200 by more than a factor of two. With the addition of the Phase II dataset taken with an upgraded detector, the median 90$\%$ confidence level half-life sensitivity of $2\nu\beta\beta$ decay to the $0^+_1$ state of $^{136}\rm Ba$ is $2.9 \times 10^{24}~\rm yr$ using a total $^{136}\rm Xe$ exposure of $234.1~\rm kg~yr$. No statistically significant evidence for $2\nu\beta\beta$ decay to the $0^+_1$ state is observed, leading to a lower limit of $T^{2\nu}_{1/2}(0^+ \rightarrow 0^+_1) > 1.4\times10^{24}~\rm yr$ at 90$\%$ confidence level, improved by 70$\%$ relative to the current world's best constraint., Comment: 9 pages, 7 figures, 2 tables

Published
2023
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37. Improved Segmentation of Deep Sulci in Cortical Gray Matter Using a Deep Learning Framework Incorporating Laplace's Equation

Author

Ravikumar, Sadhana, Ittyerah, Ranjit, Lim, Sydney, Xie, Long, Das, Sandhitsu, Khandelwal, Pulkit, Wisse, Laura E. M., Bedard, Madigan L., Robinson, John L., Schuck, Terry, Grossman, Murray, Trojanowski, John Q., Lee, Edward B., Tisdall, M. Dylan, Prabhakaran, Karthik, Detre, John A., Irwin, David J., Trotman, Winifred, Mizsei, Gabor, Artacho-Pérula, Emilio, Martin, Maria Mercedes Iñiguez de Onzono, Jiménez, Maria del Mar Arroyo, Muñoz, Monica, Romero, Francisco Javier Molina, Rabal, Maria del Pilar Marcos, Cebada-Sánchez, Sandra, González, José Carlos Delgado, de la Rosa-Prieto, Carlos, Parada, Marta Córcoles, Wolk, David A., Insausti, Ricardo, and Yushkevich, Paul A.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

When developing tools for automated cortical segmentation, the ability to produce topologically correct segmentations is important in order to compute geometrically valid morphometry measures. In practice, accurate cortical segmentation is challenged by image artifacts and the highly convoluted anatomy of the cortex itself. To address this, we propose a novel deep learning-based cortical segmentation method in which prior knowledge about the geometry of the cortex is incorporated into the network during the training process. We design a loss function which uses the theory of Laplace's equation applied to the cortex to locally penalize unresolved boundaries between tightly folded sulci. Using an ex vivo MRI dataset of human medial temporal lobe specimens, we demonstrate that our approach outperforms baseline segmentation networks, both quantitatively and qualitatively., Comment: Accepted at the 28th biennial international conference on Information Processing in Medical Imaging (IPMI 2023)

Published
2023

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