A Scalable Toolkit for Modeling 3D Surface-Based Brain Geometry

Yanghee Im; Leila Nabulsi; Melody J.Y. Kang; Sophia I. Thomopoulos; Ana M.Diaz Zuluaga; Anders M. Dale; Andriana Karuk; Annabella Di Giorgio; Benson Mwangi; Boris Gutman; Bronwyn Overs; Carlos López Jaramillo; Colm McDonald; Dan J. Stein; Dara M. Cannon; David Glahn; Diego Hidalgo-Mazzei; Diliana Pecheva; Dominik Grotegerd; Edith Pomarol-Clotet; Eduard Vieta; Emilie Olie; Enric Vilajosana Chertó; Fabio Sambataro; Fleur Howells; Freda Scheffler; Geraldo Busatto; Gerard Anmella; Giovana B. Zunta-Soares; Gloria Roberts; Henk Temmingh; Ian Gotlib; Ingrid Agartz; Jair C. Soares; James A. Karantonis; James Prisciandaro; Janice M. Fullerton; Joaquim Radua; Jonathan Savitz; Josselin Houenou; Kang Sim; Kenichiro Harada; Klaus Berger; Koji Matsuo; Lakshmi Yatham; Lars Tjelta Westlye; Lisa Eyler; Lisa Furlong; Luisa Klahn; Marco Hermesdorf; Marcus V. Zanetti; Matthew Kempton; Matthew Sacchet; Mikael Landen; Mon Ju Wu; Pedro Rosa; Philip Mitchell; Pravesh Parekh; Raymond Salvador; Rayus Kuplicki; Salvador Sarró; Susan Rossell; Tamsyn Van Rheenen; Theodore Satterthwaite; Tilo Kircher; Tomas Hajek; Udo Dannlowski; Xavier Caseras; Yuji Zhao; Ole A. Andreassen; Paul M. Thompson; Christopher R.K. Ching

doi:10.1007/978-3-032-06774-6_18

A Scalable Toolkit for Modeling 3D Surface-Based Brain Geometry

Yanghee Im
, Leila Nabulsi
, Melody J.Y. Kang
, Sophia I. Thomopoulos
, Ana M.Diaz Zuluaga
, Anders M. Dale
, Andriana Karuk
, Annabella Di Giorgio
, Benson Mwangi
, Boris Gutman
, Bronwyn Overs
, Carlos López Jaramillo
, Colm McDonald
, Dan J. Stein
, Dara M. Cannon
, David Glahn
, Diego Hidalgo-Mazzei
, Diliana Pecheva
, Dominik Grotegerd
, Edith Pomarol-Clotet

Eduard Vieta, Emilie Olie, Enric Vilajosana Chertó, Fabio Sambataro, Fleur Howells, Freda Scheffler, Geraldo Busatto, Gerard Anmella, Giovana B. Zunta-Soares, Gloria Roberts, Henk Temmingh, Ian Gotlib, Ingrid Agartz, Jair C. Soares, James A. Karantonis, James Prisciandaro, Janice M. Fullerton, Joaquim Radua, Jonathan Savitz, Josselin Houenou, Kang Sim, Kenichiro Harada, Klaus Berger, Koji Matsuo, Lakshmi Yatham, Lars Tjelta Westlye, Lisa Eyler, Lisa Furlong, Luisa Klahn, Marco Hermesdorf, Marcus V. Zanetti, Matthew Kempton, Matthew Sacchet, Mikael Landen, Mon Ju Wu, Pedro Rosa, Philip Mitchell, Pravesh Parekh, Raymond Salvador, Rayus Kuplicki, Salvador Sarró, Susan Rossell, Tamsyn Van Rheenen, Theodore Satterthwaite, Tilo Kircher, Tomas Hajek, Udo Dannlowski, Xavier Caseras, Yuji Zhao, Ole A. Andreassen, Paul M. Thompson, Christopher R.K. Ching

Research output: Chapter in Book or Conference Publication/Proceeding › Conference Publication › peer-review

Abstract

3D surface-based computational mapping is more sensitive to localized brain alterations in neurological, developmental and psychiatric conditions than traditional gross volumetric analysis, providing fine-scale 3D maps of a wide range of surface-based features. Here we introduce a scalable toolkit for large-scale computational surface analysis, with efficient algorithms for multisite data integration, statistical harmonization, accelerated multivariate statistics, and visualization. We showcase the utility of the toolkit by mapping subcortical shape variations and factors that affect them across 21 international samples from the ENIGMA Bipolar Disorder Working Group (N = 3,373).

Original language	English
Title of host publication	Shape in Medical Imaging - International Workshop, ShapeMI 2025, Held in Conjunction with MICCAI 2025, Proceedings
Editors	Christian Wachinger, Gijs Luijten, Jan Egger, Shireen Elhabian, Karthik Gopinath
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	232-246
Number of pages	15
ISBN (Print)	9783032067739
DOIs	https://doi.org/10.1007/978-3-032-06774-6_18
Publication status	Published - 2026
Event	International Workshop on Shape in Medical Imaging, ShapeMI 2025, Held in Conjunction with the 28th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2025 - Daejeon, Korea, Republic of Duration: 23 Sep 2025 → 23 Sep 2025

Publication series

Name	Lecture Notes in Computer Science
Volume	16171 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Workshop on Shape in Medical Imaging, ShapeMI 2025, Held in Conjunction with the 28th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2025
Country/Territory	Korea, Republic of
City	Daejeon
Period	23/09/25 → 23/09/25

Keywords

3D Surface Geometry
Big Data
Brain Morphometrics
Machine Learning
Visualization

Access to Document

10.1007/978-3-032-06774-6_18

Cite this

Im, Y., Nabulsi, L., Kang, M. J. Y., Thomopoulos, S. I., Zuluaga, A. M. D., Dale, A. M., Karuk, A., Di Giorgio, A., Mwangi, B., Gutman, B., Overs, B., Jaramillo, C. L., McDonald, C., Stein, D. J., Cannon, D. M., Glahn, D., Hidalgo-Mazzei, D., Pecheva, D., Grotegerd, D., ... Ching, C. R. K. (2026). A Scalable Toolkit for Modeling 3D Surface-Based Brain Geometry. In C. Wachinger, G. Luijten, J. Egger, S. Elhabian, & K. Gopinath (Eds.), Shape in Medical Imaging - International Workshop, ShapeMI 2025, Held in Conjunction with MICCAI 2025, Proceedings (pp. 232-246). (Lecture Notes in Computer Science; Vol. 16171 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-032-06774-6_18

Im, Yanghee ; Nabulsi, Leila ; Kang, Melody J.Y. et al. / A Scalable Toolkit for Modeling 3D Surface-Based Brain Geometry. Shape in Medical Imaging - International Workshop, ShapeMI 2025, Held in Conjunction with MICCAI 2025, Proceedings. editor / Christian Wachinger ; Gijs Luijten ; Jan Egger ; Shireen Elhabian ; Karthik Gopinath. Springer Science and Business Media Deutschland GmbH, 2026. pp. 232-246 (Lecture Notes in Computer Science).

@inproceedings{e08a4acc6ff94d60baf65aa8067c47a3,

title = "A Scalable Toolkit for Modeling 3D Surface-Based Brain Geometry",

abstract = "3D surface-based computational mapping is more sensitive to localized brain alterations in neurological, developmental and psychiatric conditions than traditional gross volumetric analysis, providing fine-scale 3D maps of a wide range of surface-based features. Here we introduce a scalable toolkit for large-scale computational surface analysis, with efficient algorithms for multisite data integration, statistical harmonization, accelerated multivariate statistics, and visualization. We showcase the utility of the toolkit by mapping subcortical shape variations and factors that affect them across 21 international samples from the ENIGMA Bipolar Disorder Working Group (N = 3,373).",

keywords = "3D Surface Geometry, Big Data, Brain Morphometrics, Machine Learning, Visualization",

author = "Yanghee Im and Leila Nabulsi and Kang, \{Melody J.Y.\} and Thomopoulos, \{Sophia I.\} and Zuluaga, \{Ana M.Diaz\} and Dale, \{Anders M.\} and Andriana Karuk and \{Di Giorgio\}, Annabella and Benson Mwangi and Boris Gutman and Bronwyn Overs and Jaramillo, \{Carlos L{\'o}pez\} and Colm McDonald and Stein, \{Dan J.\} and Cannon, \{Dara M.\} and David Glahn and Diego Hidalgo-Mazzei and Diliana Pecheva and Dominik Grotegerd and Edith Pomarol-Clotet and Eduard Vieta and Emilie Olie and Chert{\'o}, \{Enric Vilajosana\} and Fabio Sambataro and Fleur Howells and Freda Scheffler and Geraldo Busatto and Gerard Anmella and Zunta-Soares, \{Giovana B.\} and Gloria Roberts and Henk Temmingh and Ian Gotlib and Ingrid Agartz and Soares, \{Jair C.\} and Karantonis, \{James A.\} and James Prisciandaro and Fullerton, \{Janice M.\} and Joaquim Radua and Jonathan Savitz and Josselin Houenou and Kang Sim and Kenichiro Harada and Klaus Berger and Koji Matsuo and Lakshmi Yatham and Westlye, \{Lars Tjelta\} and Lisa Eyler and Lisa Furlong and Luisa Klahn and Marco Hermesdorf and Zanetti, \{Marcus V.\} and Matthew Kempton and Matthew Sacchet and Mikael Landen and Wu, \{Mon Ju\} and Pedro Rosa and Philip Mitchell and Pravesh Parekh and Raymond Salvador and Rayus Kuplicki and Salvador Sarr{\'o} and Susan Rossell and \{Van Rheenen\}, Tamsyn and Theodore Satterthwaite and Tilo Kircher and Tomas Hajek and Udo Dannlowski and Xavier Caseras and Yuji Zhao and Andreassen, \{Ole A.\} and Thompson, \{Paul M.\} and Ching, \{Christopher R.K.\}",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.; International Workshop on Shape in Medical Imaging, ShapeMI 2025, Held in Conjunction with the 28th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2025 ; Conference date: 23-09-2025 Through 23-09-2025",

year = "2026",

doi = "10.1007/978-3-032-06774-6\_18",

language = "English",

isbn = "9783032067739",

series = "Lecture Notes in Computer Science",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "232--246",

editor = "Christian Wachinger and Gijs Luijten and Jan Egger and Shireen Elhabian and Karthik Gopinath",

booktitle = "Shape in Medical Imaging - International Workshop, ShapeMI 2025, Held in Conjunction with MICCAI 2025, Proceedings",

}

Im, Y, Nabulsi, L, Kang, MJY, Thomopoulos, SI, Zuluaga, AMD, Dale, AM, Karuk, A, Di Giorgio, A, Mwangi, B, Gutman, B, Overs, B, Jaramillo, CL, McDonald, C, Stein, DJ, Cannon, DM, Glahn, D, Hidalgo-Mazzei, D, Pecheva, D, Grotegerd, D, Pomarol-Clotet, E, Vieta, E, Olie, E, Chertó, EV, Sambataro, F, Howells, F, Scheffler, F, Busatto, G, Anmella, G, Zunta-Soares, GB, Roberts, G, Temmingh, H, Gotlib, I, Agartz, I, Soares, JC, Karantonis, JA, Prisciandaro, J, Fullerton, JM, Radua, J, Savitz, J, Houenou, J, Sim, K, Harada, K, Berger, K, Matsuo, K, Yatham, L, Westlye, LT, Eyler, L, Furlong, L, Klahn, L, Hermesdorf, M, Zanetti, MV, Kempton, M, Sacchet, M, Landen, M, Wu, MJ, Rosa, P, Mitchell, P, Parekh, P, Salvador, R, Kuplicki, R, Sarró, S, Rossell, S, Van Rheenen, T, Satterthwaite, T, Kircher, T, Hajek, T, Dannlowski, U, Caseras, X, Zhao, Y, Andreassen, OA, Thompson, PM & Ching, CRK 2026, A Scalable Toolkit for Modeling 3D Surface-Based Brain Geometry. in C Wachinger, G Luijten, J Egger, S Elhabian & K Gopinath (eds), Shape in Medical Imaging - International Workshop, ShapeMI 2025, Held in Conjunction with MICCAI 2025, Proceedings. Lecture Notes in Computer Science, vol. 16171 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 232-246, International Workshop on Shape in Medical Imaging, ShapeMI 2025, Held in Conjunction with the 28th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2025, Daejeon, Korea, Republic of, 23/09/25. https://doi.org/10.1007/978-3-032-06774-6_18

A Scalable Toolkit for Modeling 3D Surface-Based Brain Geometry. / Im, Yanghee; Nabulsi, Leila; Kang, Melody J.Y. et al.
Shape in Medical Imaging - International Workshop, ShapeMI 2025, Held in Conjunction with MICCAI 2025, Proceedings. ed. / Christian Wachinger; Gijs Luijten; Jan Egger; Shireen Elhabian; Karthik Gopinath. Springer Science and Business Media Deutschland GmbH, 2026. p. 232-246 (Lecture Notes in Computer Science; Vol. 16171 LNCS).

Research output: Chapter in Book or Conference Publication/Proceeding › Conference Publication › peer-review

TY - GEN

T1 - A Scalable Toolkit for Modeling 3D Surface-Based Brain Geometry

AU - Im, Yanghee

AU - Nabulsi, Leila

AU - Kang, Melody J.Y.

AU - Thomopoulos, Sophia I.

AU - Zuluaga, Ana M.Diaz

AU - Dale, Anders M.

AU - Karuk, Andriana

AU - Di Giorgio, Annabella

AU - Mwangi, Benson

AU - Gutman, Boris

AU - Overs, Bronwyn

AU - Jaramillo, Carlos López

AU - McDonald, Colm

AU - Stein, Dan J.

AU - Cannon, Dara M.

AU - Glahn, David

AU - Hidalgo-Mazzei, Diego

AU - Pecheva, Diliana

AU - Grotegerd, Dominik

AU - Pomarol-Clotet, Edith

AU - Vieta, Eduard

AU - Olie, Emilie

AU - Chertó, Enric Vilajosana

AU - Sambataro, Fabio

AU - Howells, Fleur

AU - Scheffler, Freda

AU - Busatto, Geraldo

AU - Anmella, Gerard

AU - Zunta-Soares, Giovana B.

AU - Roberts, Gloria

AU - Temmingh, Henk

AU - Gotlib, Ian

AU - Agartz, Ingrid

AU - Soares, Jair C.

AU - Karantonis, James A.

AU - Prisciandaro, James

AU - Fullerton, Janice M.

AU - Radua, Joaquim

AU - Savitz, Jonathan

AU - Houenou, Josselin

AU - Sim, Kang

AU - Harada, Kenichiro

AU - Berger, Klaus

AU - Matsuo, Koji

AU - Yatham, Lakshmi

AU - Westlye, Lars Tjelta

AU - Eyler, Lisa

AU - Furlong, Lisa

AU - Klahn, Luisa

AU - Hermesdorf, Marco

AU - Zanetti, Marcus V.

AU - Kempton, Matthew

AU - Sacchet, Matthew

AU - Landen, Mikael

AU - Wu, Mon Ju

AU - Rosa, Pedro

AU - Mitchell, Philip

AU - Parekh, Pravesh

AU - Salvador, Raymond

AU - Kuplicki, Rayus

AU - Sarró, Salvador

AU - Rossell, Susan

AU - Van Rheenen, Tamsyn

AU - Satterthwaite, Theodore

AU - Kircher, Tilo

AU - Hajek, Tomas

AU - Dannlowski, Udo

AU - Caseras, Xavier

AU - Zhao, Yuji

AU - Andreassen, Ole A.

AU - Thompson, Paul M.

AU - Ching, Christopher R.K.

PY - 2026

Y1 - 2026

N2 - 3D surface-based computational mapping is more sensitive to localized brain alterations in neurological, developmental and psychiatric conditions than traditional gross volumetric analysis, providing fine-scale 3D maps of a wide range of surface-based features. Here we introduce a scalable toolkit for large-scale computational surface analysis, with efficient algorithms for multisite data integration, statistical harmonization, accelerated multivariate statistics, and visualization. We showcase the utility of the toolkit by mapping subcortical shape variations and factors that affect them across 21 international samples from the ENIGMA Bipolar Disorder Working Group (N = 3,373).

AB - 3D surface-based computational mapping is more sensitive to localized brain alterations in neurological, developmental and psychiatric conditions than traditional gross volumetric analysis, providing fine-scale 3D maps of a wide range of surface-based features. Here we introduce a scalable toolkit for large-scale computational surface analysis, with efficient algorithms for multisite data integration, statistical harmonization, accelerated multivariate statistics, and visualization. We showcase the utility of the toolkit by mapping subcortical shape variations and factors that affect them across 21 international samples from the ENIGMA Bipolar Disorder Working Group (N = 3,373).

KW - 3D Surface Geometry

KW - Big Data

KW - Brain Morphometrics

KW - Machine Learning

KW - Visualization

UR - https://www.scopus.com/pages/publications/105020023725

U2 - 10.1007/978-3-032-06774-6_18

DO - 10.1007/978-3-032-06774-6_18

M3 - Conference Publication

AN - SCOPUS:105020023725

SN - 9783032067739

T3 - Lecture Notes in Computer Science

SP - 232

EP - 246

BT - Shape in Medical Imaging - International Workshop, ShapeMI 2025, Held in Conjunction with MICCAI 2025, Proceedings

A2 - Wachinger, Christian

A2 - Luijten, Gijs

A2 - Egger, Jan

A2 - Elhabian, Shireen

A2 - Gopinath, Karthik

PB - Springer Science and Business Media Deutschland GmbH

T2 - International Workshop on Shape in Medical Imaging, ShapeMI 2025, Held in Conjunction with the 28th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2025

Y2 - 23 September 2025 through 23 September 2025

ER -

Im Y, Nabulsi L, Kang MJY, Thomopoulos SI, Zuluaga AMD, Dale AM et al. A Scalable Toolkit for Modeling 3D Surface-Based Brain Geometry. In Wachinger C, Luijten G, Egger J, Elhabian S, Gopinath K, editors, Shape in Medical Imaging - International Workshop, ShapeMI 2025, Held in Conjunction with MICCAI 2025, Proceedings. Springer Science and Business Media Deutschland GmbH. 2026. p. 232-246. (Lecture Notes in Computer Science). doi: 10.1007/978-3-032-06774-6_18

A Scalable Toolkit for Modeling 3D Surface-Based Brain Geometry

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Keywords

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