Search Results - "Shinohara, T"

SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network by Hu, Jian, Li, Xiangjie, Coleman, Kyle, Schroeder, Amelia, Ma, Nan, Irwin, David J., Lee, Edward B., Shinohara, Russell T., Li, Mingyao

“…Recent advances in spatially resolved transcriptomics (SRT) technologies have enabled comprehensive characterization of gene expression patterns in the context…”
Get full text

Interpreting support vector machine models for multivariate group wise analysis in neuroimaging by Gaonkar, Bilwaj, T. Shinohara, Russell, Davatzikos, Christos

“…•Support vector machines (SVM) use multivariate imaging information for diagnosis.•Approximate SVM permutation tests for population statistics.•Improved…”
Get full text

Harmonization of cortical thickness measurements across scanners and sites by Fortin, Jean-Philippe, Cullen, Nicholas, Sheline, Yvette I., Taylor, Warren D., Aselcioglu, Irem, Cook, Philip A., Adams, Phil, Cooper, Crystal, Fava, Maurizio, McGrath, Patrick J., McInnis, Melvin, Phillips, Mary L., Trivedi, Madhukar H., Weissman, Myrna M., Shinohara, Russell T.

“…With the proliferation of multi-site neuroimaging studies, there is a greater need for handling non-biological variance introduced by differences in MRI…”
Get full text

Statistical harmonization corrects site effects in functional connectivity measurements from multi‐site fMRI data by Yu, Meichen, Linn, Kristin A., Cook, Philip A., Phillips, Mary L., McInnis, Melvin, Fava, Maurizio, Trivedi, Madhukar H., Weissman, Myrna M., Shinohara, Russell T., Sheline, Yvette I.

“…Acquiring resting‐state functional magnetic resonance imaging (fMRI) datasets at multiple MRI scanners and clinical sites can improve statistical power and…”
Get full text

Harmonization of multi-site diffusion tensor imaging data by Fortin, Jean-Philippe, Parker, Drew, Tunç, Birkan, Watanabe, Takanori, Elliott, Mark A., Ruparel, Kosha, Roalf, David R., Satterthwaite, Theodore D., Gur, Ruben C., Gur, Raquel E., Schultz, Robert T., Verma, Ragini, Shinohara, Russell T.

“…Diffusion tensor imaging (DTI) is a well-established magnetic resonance imaging (MRI) technique used for studying microstructural changes in the white matter…”
Get full text

Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity by Ciric, Rastko, Wolf, Daniel H., Power, Jonathan D., Roalf, David R., Baum, Graham L., Ruparel, Kosha, Shinohara, Russell T., Elliott, Mark A., Eickhoff, Simon B., Davatzikos, Christos, Gur, Ruben C., Gur, Raquel E., Bassett, Danielle S., Satterthwaite, Theodore D.

“…Since initial reports regarding the impact of motion artifact on measures of functional connectivity, there has been a proliferation of participant-level…”
Get full text

Longitudinal ComBat: A method for harmonizing longitudinal multi-scanner imaging data by Beer, Joanne C., Tustison, Nicholas J., Cook, Philip A., Davatzikos, Christos, Sheline, Yvette I., Shinohara, Russell T., Linn, Kristin A.

“…While aggregation of neuroimaging datasets from multiple sites and scanners can yield increased statistical power, it also presents challenges due to…”
Get full text

Large-scale Radiomic Profiling of Recurrent Glioblastoma Identifies an Imaging Predictor for Stratifying Anti-Angiogenic Treatment Response by Kickingereder, Philipp, Götz, Michael, Muschelli, John, Wick, Antje, Neuberger, Ulf, Shinohara, Russell T, Sill, Martin, Nowosielski, Martha, Schlemmer, Heinz-Peter, Radbruch, Alexander, Wick, Wolfgang, Bendszus, Martin, Maier-Hein, Klaus H, Bonekamp, David

“…Antiangiogenic treatment with bevacizumab, a mAb to the VEGF, is the single most widely used therapeutic agent for patients with recurrent glioblastoma. A…”
Get full text

Linked dimensions of psychopathology and connectivity in functional brain networks by Xia, Cedric Huchuan, Ma, Zongming, Ciric, Rastko, Gu, Shi, Betzel, Richard F., Kaczkurkin, Antonia N., Calkins, Monica E., Cook, Philip A., García de la Garza, Angel, Vandekar, Simon N., Cui, Zaixu, Moore, Tyler M., Roalf, David R., Ruparel, Kosha, Wolf, Daniel H., Davatzikos, Christos, Gur, Ruben C., Gur, Raquel E., Shinohara, Russell T., Bassett, Danielle S., Satterthwaite, Theodore D.

“…Neurobiological abnormalities associated with psychiatric disorders do not map well to existing diagnostic categories. High co-morbidity suggests dimensional…”
Get full text

Multidimensional brain-age prediction reveals altered brain developmental trajectory in psychiatric disorders by Niu, Xin, Taylor, Alexei, Shinohara, Russell T, Kounios, John, Zhang, Fengqing

“…Brain-age prediction has emerged as a novel approach for studying brain development. However, brain regions change in different ways and at different rates…”
Get full text

Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning by Chand, Ganesh B, Dwyer, Dominic B, Erus, Guray, Sotiras, Aristeidis, Varol, Erdem, Srinivasan, Dhivya, Doshi, Jimit, Pomponio, Raymond, Pigoni, Alessandro, Dazzan, Paola, Kahn, Rene S, Schnack, Hugo G, Zanetti, Marcus V, Meisenzahl, Eva, Busatto, Geraldo F, Crespo-Facorro, Benedicto, Pantelis, Christos, Wood, Stephen J, Zhuo, Chuanjun, Shinohara, Russell T, Shou, Haochang, Fan, Yong, Gur, Ruben C, Gur, Raquel E, Satterthwaite, Theodore D, Koutsouleris, Nikolaos, Wolf, Daniel H, Davatzikos, Christos

“…Neurobiological heterogeneity in schizophrenia is poorly understood and confounds current analyses. We investigated neuroanatomical subtypes in a…”
Get full text

Image harmonization: A review of statistical and deep learning methods for removing batch effects and evaluation metrics for effective harmonization by Hu, Fengling, Chen, Andrew A., Horng, Hannah, Bashyam, Vishnu, Davatzikos, Christos, Alexander-Bloch, Aaron, Li, Mingyao, Shou, Haochang, Satterthwaite, Theodore D., Yu, Meichen, Shinohara, Russell T.

“…•Batch effects introduce significant confounding in multi-batch neuroimaging data.•Removal of batch effects is critical for reproducibility and…”
Get full text

Modular Segregation of Structural Brain Networks Supports the Development of Executive Function in Youth by Baum, Graham L., Ciric, Rastko, Roalf, David R., Betzel, Richard F., Moore, Tyler M., Shinohara, Russell T., Kahn, Ari E., Vandekar, Simon N., Rupert, Petra E., Quarmley, Megan, Cook, Philip A., Elliott, Mark A., Ruparel, Kosha, Gur, Raquel E., Gur, Ruben C., Bassett, Danielle S., Satterthwaite, Theodore D.

“…The human brain is organized into large-scale functional modules that have been shown to evolve in childhood and adolescence. However, it remains unknown…”
Get full text

Childhood trauma history is linked to abnormal brain connectivity in major depression by Yu, Meichen, Linn, Kristin A., Shinohara, Russell T., Oathes, Desmond J., Cook, Philip A., Duprat, Romain, Moore, Tyler M., Oquendo, Maria A., Phillips, Mary L., McInnis, Melvin, Fava, Maurizio, Trivedi, Madhukar H., McGrath, Patrick, Parsey, Ramin, Weissman, Myrna M., Sheline, Yvette I.

“…Patients with major depressive disorder (MDD) present with heterogeneous symptom profiles, while neurobiological mechanisms are still largely unknown. Brain…”
Get full text

Spatial distribution of interictal spikes fluctuates over time and localizes seizure onset by Conrad, Erin C, Tomlinson, Samuel B, Wong, Jeremy N, Oechsel, Kelly F, Shinohara, Russell T, Litt, Brian, Davis, Kathryn A, Marsh, Eric D

“…The location of interictal spikes is used to aid surgical planning in patients with medically refractory epilepsy; however, their spatial and temporal dynamics…”
Get full text

Normative brain size variation and brain shape diversity in humans by Reardon, P K, Seidlitz, Jakob, Vandekar, Simon, Liu, Siyuan, Patel, Raihaan, Park, Min Tae M, Alexander-Bloch, Aaron, Clasen, Liv S, Blumenthal, Jonathan D, Lalonde, Francois M, Giedd, Jay N, Gur, Ruben C, Gur, Raquel E, Lerch, Jason P, Chakravarty, M Mallar, Satterthwaite, Theodore D, Shinohara, Russell T, Raznahan, Armin

“…Brain size variation over primate evolution and human development is associated with shifts in the proportions of different brain regions. Individual brain…”
Get full text

The central vein sign and its clinical evaluation for the diagnosis of multiple sclerosis: a consensus statement from the North American Imaging in Multiple Sclerosis Cooperative by Sati, Pascal, Oh, Jiwon, Constable, R. Todd, Evangelou, Nikos, Guttmann, Charles R. G., Henry, Roland G., Klawiter, Eric C., Mainero, Caterina, Massacesi, Luca, McFarland, Henry, Nelson, Flavia, Ontaneda, Daniel, Rauscher, Alexander, Rooney, William D., Samaraweera, Amal P. R., Shinohara, Russell T., Sobel, Raymond A., Solomon, Andrew J., Treaba, Constantina A., Wuerfel, Jens, Zivadinov, Robert, Sicotte, Nancy L., Pelletier, Daniel, Reich, Daniel S.

“…The central vein sign (CVS) has been proposed as a novel MRI biomarker to improve the accuracy and speed of multiple sclerosis (MS) diagnosis. This Consensus…”
Get full text

Generalized ComBat harmonization methods for radiomic features with multi-modal distributions and multiple batch effects by Horng, Hannah, Singh, Apurva, Yousefi, Bardia, Cohen, Eric A., Haghighi, Babak, Katz, Sharyn, Noël, Peter B., Shinohara, Russell T., Kontos, Despina

“…Radiomic features have a wide range of clinical applications, but variability due to image acquisition factors can affect their performance. The harmonization…”
Get full text

Treatment pathway of bone sarcoma in children, adolescents, and young adults by Reed, Damon R., Hayashi, Masanori, Wagner, Lars, Binitie, Odion, Steppan, Diana A., Brohl, Andrew S., Shinohara, Eric T., Bridge, Julia A., Loeb, David M., Borinstein, Scott C., Isakoff, Michael S.

“…When pediatric, adolescent, and young adult patients present with a bone sarcoma, treatment decisions, especially after relapse, are complex and require a…”
Get full text

Removing inter-subject technical variability in magnetic resonance imaging studies by Fortin, Jean-Philippe, Sweeney, Elizabeth M., Muschelli, John, Crainiceanu, Ciprian M., Shinohara, Russell T.

“…Magnetic resonance imaging (MRI) intensities are acquired in arbitrary units, making scans non-comparable across sites and between subjects. Intensity…”
Get full text