Search Results for author: Jeff Lichtman

Found 8 papers, 4 papers with code

Two Stream Active Query Suggestion for Active Learning in Connectomics

no code implementations • ECCV 2020 • Zudi Lin, Donglai Wei, Won-Dong Jang, Siyan Zhou, Xupeng Chen, Xueying Wang, Richard Schalek, Daniel Berger, Brian Matejek, Lee Kamentsky, Adi Peleg, Daniel Haehn, Thouis Jones, Toufiq Parag, Jeff Lichtman, Hanspeter Pfister

As a use case, we build an end-to-end active learning framework with our query suggestion method for 3D synapse detection and mitochondria segmentation in connectomics.

Active Learning Image Classification +1

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TriSAM: Tri-Plane SAM for zero-shot cortical blood vessel segmentation in VEM images

no code implementations • 25 Jan 2024 • Jia Wan, Wanhua Li, Jason Ken Adhinarta, Atmadeep Banerjee, Evelina Sjostedt, Jingpeng Wu, Jeff Lichtman, Hanspeter Pfister, Donglai Wei

Furthermore, we developed a zero-shot cortical blood vessel segmentation method named TriSAM, which leverages the powerful segmentation model SAM for 3D segmentation.

Benchmarking Segmentation

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PyTorch Connectomics: A Scalable and Flexible Segmentation Framework for EM Connectomics

1 code implementation • 10 Dec 2021 • Zudi Lin, Donglai Wei, Jeff Lichtman, Hanspeter Pfister

We present PyTorch Connectomics (PyTC), an open-source deep-learning framework for the semantic and instance segmentation of volumetric microscopy images, built upon PyTorch.

Instance Segmentation Segmentation +1

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NucMM Dataset: 3D Neuronal Nuclei Instance Segmentation at Sub-Cubic Millimeter Scale

1 code implementation • 13 Jul 2021 • Zudi Lin, Donglai Wei, Mariela D. Petkova, Yuelong Wu, Zergham Ahmed, Krishna Swaroop K, Silin Zou, Nils Wendt, Jonathan Boulanger-Weill, Xueying Wang, Nagaraju Dhanyasi, Ignacio Arganda-Carreras, Florian Engert, Jeff Lichtman, Hanspeter Pfister

Segmenting 3D cell nuclei from microscopy image volumes is critical for biological and clinical analysis, enabling the study of cellular expression patterns and cell lineages.

Instance Segmentation Representation Learning +1

163

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AxonEM Dataset: 3D Axon Instance Segmentation of Brain Cortical Regions

1 code implementation • 12 Jul 2021 • Donglai Wei, Kisuk Lee, Hanyu Li, Ran Lu, J. Alexander Bae, Zequan Liu, Lifu Zhang, Márcia dos Santos, Zudi Lin, Thomas Uram, Xueying Wang, Ignacio Arganda-Carreras, Brian Matejek, Narayanan Kasthuri, Jeff Lichtman, Hanspeter Pfister

Electron microscopy (EM) enables the reconstruction of neural circuits at the level of individual synapses, which has been transformative for scientific discoveries.

Instance Segmentation Segmentation +1

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MitoEM Dataset: Large-scale 3D Mitochondria Instance Segmentation from EM Images

1 code implementation • Medical Image Computing and Computer Assisted Intervention 2020 • Donglai Wei, Zudi Lin, Daniel Franco-Barranco, Nils Wendt, Xingyu Liu, Wenjie Yin, Xin Huang, Aarush Gupta, Won-Dong Jang, Xueying Wang, Ignacio Arganda-Carreras, Jeff Lichtman, Hanspeter Pfister

On MitoEM, we find existing instance segmentation methods often fail to correctly segment mitochondria with complex shapes or close contacts with other instances.

Ranked #2 on 3D Instance Segmentation on MitoEM (AP75-R-Test metric)