Deposition

Octopi and TopCup particle picks for a self-configuring in situ cryoET structure-determination workflow

Deposition ID:CZCDP-10358

Release Date: 2026-06-24

Last Modified: 2026-06-24

key visualization for Octopi and TopCup particle picks for a self-configuring in situ cryoET structure-determination workflow

Photo Caption: Central slab of 4 representative tomograms with selected sets of annotations.

Deposition Overview

Particle picks produced by Octopi and TopCup, two deep-learning particle-detection models from the self-configuring in situ cryoET structure-determination workflow (Octopi + py2rely). Octopi is a self-configuring 3D U-Net whose architecture/hyperparameters are selected per dataset by Bayesian optimization; TopCup is an open re-implementation of the top-ranked 2024-2025 Kaggle CryoET Object Identification Challenge solution, used as a fixed-architecture baseline. Picks are deposited for: GroEL in in-situ E. coli; apo-ferritin, beta-amylase, beta-galactosidase, ribosome, thyroglobulin and virus-like particle in the Phantom/ML-Challenge datasets (both Octopi and TopCup); cytosolic and membrane-bound ribosomes in unroofed cells; and V-ATPase on isolated synaptic vesicles. All picks are model predictions validated by subtomogram averaging with py2rely (RELION-5).

Authors

Deposition Data

Annotations:6,372

Tomograms:0

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Methods Summary

Annotations	Method Type	Method Details	Method Links
2968	Automated	Automated particle detection with Octopi, a self-configuring supervised 3D U-Net (built on MONAI primitives) whose architecture and training hyperparameters are selected per dataset via Bayesian optimization (Optuna, TPE sampler). Particle coordinates were extracted from the predicted per-class segmentation masks using a watershed-based peak detector, retaining candidates whose effective radius is 50-100% of the specified particle radius. Coordinates were validated by subtomogram averaging with py2rely (RELION-5).	Source Code:copick +4 more
301	Automated	Automated particle detection with Octopi, a self-configuring supervised 3D U-Net (built on MONAI primitives) whose architecture and training hyperparameters are selected per dataset via Bayesian optimization (Optuna, TPE sampler). Particle coordinates were extracted from the predicted per-class segmentation masks using a watershed-based peak detector, retaining candidates whose effective radius is 50-100% of the specified particle radius. Coordinates were validated by subtomogram averaging with py2rely (RELION-5). For this membrane-associated target, membrane-proximal particles were separated from distal ones by Euclidean distance to MemBrain-seg-segmented membranes, and each pick was assigned an initial orientation from the local membrane normal.	Source Code:copick +5 more
2841	Automated	Automated particle detection with TopCup, an open re-implementation of the top-ranked solution of the 2024-2025 Kaggle CryoET Object Identification Challenge: a 3D U-Net (MONAI FlexibleUNet with a ResNet/EfficientNet encoder) with a segmentation head at each decoder level (deep supervision), trained on binary-sphere targets with dense cross-entropy loss. Coordinates were validated by subtomogram averaging with py2rely (RELION-5).	Source Code:copick +4 more
262	Automated	MemBrain-seg membrane segmentation at the native tomogram resolution, cleaned by clipping to the sample boundaries.	Source Code:copick +1 more

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6,372 of 6,372 Annotations

Annotation Name	Object Shape Type	Method Type	Deposited In
169virus-like capsid Annotation ID: AN-181572	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_9
168virus-like capsid Annotation ID: AN-181571	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_9
167Thyroglobulin Annotation ID: AN-181570	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_9
166Thyroglobulin Annotation ID: AN-181569	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_9
165cytosolic ribosome Annotation ID: AN-181568	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_9
164cytosolic ribosome Annotation ID: AN-181567	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_9
163Beta-galactosidase Annotation ID: AN-181566	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_9
162Beta-galactosidase Annotation ID: AN-181565	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_9
161Beta-amylase Annotation ID: AN-181564	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_9
160Beta-amylase Annotation ID: AN-181563	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_9
159ferritin complex Annotation ID: AN-181562	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_9
158ferritin complex Annotation ID: AN-181561	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_9
169virus-like capsid Annotation ID: AN-181560	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_8
168virus-like capsid Annotation ID: AN-181559	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_8
167Thyroglobulin Annotation ID: AN-181558	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_8
166Thyroglobulin Annotation ID: AN-181557	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_8
165cytosolic ribosome Annotation ID: AN-181556	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_8
164cytosolic ribosome Annotation ID: AN-181555	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_8
163Beta-galactosidase Annotation ID: AN-181554	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_8
162Beta-galactosidase Annotation ID: AN-181553	OrientedPoint	Automated	Dataset: CZII - CryoET Object Identification Challenge - Private Test Dataset Run: TS_9_8