TY - GEN
T1 - Real-Time Alignment for Connectomics
AU - Goyal, Neha
AU - Hussain, Yahiya
AU - Yang, Gianna G.
AU - Haehn, Daniel
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - In Connectomics, researchers are creating the brain’s wiring diagram at nanometer resolution. As part of this processing workflow, 2D electron microscopy (EM) images must be aligned to 3D volumes. However, existing alignment methods are computationally expensive and can take a long time. We hypothesize that adding biological features improve and accelerate the alignment procedure. Since especially mitochondria can be detected accurately and fast, we propose a new alignment method, MITO, that uses these structures as landmark points. With MITO, we can decrease the alignment time by 27%, and our experiments indicate a throughput of 33 Megapixels/s, which is faster than the acquisition speed of current microscopes. We can align an image volume of 1268 × 1524 × 160 voxels in less than 12 s. We compare our method to the following feature generators: ORB, BRISK, FAST, and FREAK.
AB - In Connectomics, researchers are creating the brain’s wiring diagram at nanometer resolution. As part of this processing workflow, 2D electron microscopy (EM) images must be aligned to 3D volumes. However, existing alignment methods are computationally expensive and can take a long time. We hypothesize that adding biological features improve and accelerate the alignment procedure. Since especially mitochondria can be detected accurately and fast, we propose a new alignment method, MITO, that uses these structures as landmark points. With MITO, we can decrease the alignment time by 27%, and our experiments indicate a throughput of 33 Megapixels/s, which is faster than the acquisition speed of current microscopes. We can align an image volume of 1268 × 1524 × 160 voxels in less than 12 s. We compare our method to the following feature generators: ORB, BRISK, FAST, and FREAK.
KW - Feature matching
KW - Image alignment
KW - Registration
UR - https://www.scopus.com/pages/publications/85135089274
UR - https://www.scopus.com/pages/publications/85135089274#tab=citedBy
U2 - 10.1007/978-3-031-11203-4_25
DO - 10.1007/978-3-031-11203-4_25
M3 - Conference contribution
AN - SCOPUS:85135089274
SN - 9783031112027
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 211
EP - 214
BT - Biomedical Image Registration - 10th International Workshop, WBIR 2022, Proceedings
A2 - Hering, Alessa
A2 - Schnabel, Julia
A2 - Zhang, Miaomiao
A2 - Ferrante, Enzo
A2 - Heinrich, Mattias
A2 - Rueckert, Daniel
PB - Springer Science and Business Media Deutschland GmbH
T2 - 10th International Workshop on Biomedical Image Registration, WBIR 2020
Y2 - 10 July 2022 through 12 July 2022
ER -