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Daniel Haehn
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Journal Articles
- 2023
- [j9]Navaneethakrishna Makaram, Sarvagya Gupta, Matthew Pesce, Jeffrey Bolton, Scellig S. Stone, Daniel Haehn, Marc Pomplun, Christos L. Papadelis, Phillip L. Pearl, Alexander Rotenberg, Patricia Ellen Grant, Eleonora Tamilia:
Deep Learning-Based Visual Complexity Analysis of Electroencephalography Time-Frequency Images: Can It Localize the Epileptogenic Zone in the Brain? Algorithms 16(12): 567 (2023) - 2022
- [j8]Jay Burkhardt, Aaryaman Sharma, Jack Tan, Loraine Franke, Jahnavi Leburu, Jay Jeschke, Sasha Devore, Daniel Friedman, Jingyun Chen, Daniel Haehn:
N-Tools-Browser: Web-Based Visualization of Electrocorticography Data for Epilepsy Surgery. Frontiers Bioinform. 2 (2022) - [j7]Nalini M. Singh, Jordan B. Harrod, Sandya Subramanian, Mitchell Robinson, Ken Chang, Suheyla Cetin Karayumak, Adrian Vasile Dalca, Simon B. Eickhoff, Michael Fox, Loraine Franke, Polina Golland, Daniel Haehn, Juan Eugenio Iglesias, Lauren J. O'Donnell, Yangming Ou, Yogesh Rathi, Shan H. Siddiqi, Haoqi Sun, M. Brandon Westover, Susan L. Whitfield-Gabrieli, Randy L. Gollub:
How Machine Learning is Powering Neuroimaging to Improve Brain Health. Neuroinformatics 20(4): 943-964 (2022) - 2020
- [j6]Fritz Lekschas, Brant Peterson, Daniel Haehn, Eric Ma, Nils Gehlenborg, Hanspeter Pfister:
Peax : Interactive Visual Pattern Search in Sequential Data Using Unsupervised Deep Representation Learning. Comput. Graph. Forum 39(3): 167-179 (2020) - [j5]Loraine Franke, Daniel Haehn:
Modern Scientific Visualizations on the Web. Informatics 7(4): 37 (2020) - 2019
- [j4]Daniel Haehn, James Tompkin, Hanspeter Pfister:
Evaluating 'Graphical Perception' with CNNs. IEEE Trans. Vis. Comput. Graph. 25(1): 641-650 (2019) - 2017
- [j3]Daniel Haehn, John Hoffer, Brian Matejek, Adi Suissa-Peleg, Ali K. Al-Awami, Lee Kamentsky, Felix Gonda, Eagon Meng, William Zhang, Richard Schalek, Alyssa Wilson, Toufiq Parag, Johanna Beyer, Verena Kaynig, Thouis R. Jones, James Tompkin, Markus Hadwiger, Jeff W. Lichtman, Hanspeter Pfister:
Scalable Interactive Visualization for Connectomics. Informatics 4(3): 29 (2017) - 2016
- [j2]Ali K. Al-Awami, Johanna Beyer, Daniel Haehn, Narayanan Kasthuri, Jeff W. Lichtman, Hanspeter Pfister, Markus Hadwiger:
NeuroBlocks - Visual Tracking of Segmentation and Proofreading for Large Connectomics Projects. IEEE Trans. Vis. Comput. Graph. 22(1): 738-746 (2016) - 2014
- [j1]Daniel Haehn, Seymour Knowles-Barley, Mike Roberts, Johanna Beyer, Narayanan Kasthuri, Jeff W. Lichtman, Hanspeter Pfister:
Design and Evaluation of Interactive Proofreading Tools for Connectomics. IEEE Trans. Vis. Comput. Graph. 20(12): 2466-2475 (2014)
Conference and Workshop Papers
- 2023
- [c15]Kristin Qi, Jiali Cheng, Daniel Haehn:
Lesion Search with Self-supervised Learning. Tiny Papers @ ICLR 2023 - [c14]Daniel Karl I. Weidele, Shazia Afzal, Abel N. Valente, Cole Makuch, Owen Cornec, Long Vu, Dharmashankar Subramanian, Werner Geyer, Rahul Nair, Inge Vejsbjerg, Radu Marinescu, Paulito P. Palmes, Elizabeth M. Daly, Loraine Franke, Daniel Haehn:
AutoDOViz: Human-Centered Automation for Decision Optimization. IUI 2023: 664-680 - 2022
- [c13]Neha Goyal, Yahiya Hussain, Gianna G. Yang, Daniel Haehn:
Real-Time Alignment for Connectomics. WBIR 2022: 211-214 - 2021
- [c12]Loraine Franke, Daniel Karl I. Weidele, Fan Zhang, Suheyla Cetin Karayumak, Steve Pieper, Lauren J. O'Donnell, Yogesh Rathi, Daniel Haehn:
FiberStars: Visual Comparison of Diffusion Tractography Data between Multiple Subjects. PacificVis 2021: 116-125 - [c11]Bella Baidak, Yahiya Hussain, Emma Kelminson, Thouis R. Jones, Loraine Franke, Daniel Haehn:
CellProfiler Analyst Web (CPAW) - Exploration, analysis, and classification of biological images on the web. IEEE VIS (Short Papers) 2021: 131-135 - 2020
- [c10]Zudi Lin, Donglai Wei, Won-Dong Jang, Siyan Zhou, Xupeng Chen, Xueying Wang, Richard Schalek, Daniel R. Berger, Brian Matejek, Lee Kamentsky, Adi Suissa-Peleg, Daniel Haehn, Thouis R. Jones, Toufiq Parag, Jeff Lichtman, Hanspeter Pfister:
Two Stream Active Query Suggestion for Active Learning in Connectomics. ECCV (18) 2020: 103-120 - [c9]Daniel Haehn, Loraine Franke, Fan Zhang, Suheyla Cetin Karayumak, Steve Pieper, Lauren J. O'Donnell, Yogesh Rathi:
TRAKO: Efficient Transmission of Tractography Data for Visualization. MICCAI (7) 2020: 322-332 - [c8]Vincent Casser, Kai Kang, Hanspeter Pfister, Daniel Haehn:
Fast Mitochondria Detection for Connectomics. MIDL 2020: 111-120 - 2019
- [c7]Brian Matejek, Daniel Haehn, Haidong Zhu, Donglai Wei, Toufiq Parag, Hanspeter Pfister:
Biologically-Constrained Graphs for Global Connectomics Reconstruction. CVPR 2019: 2089-2098 - 2018
- [c6]Daniel Haehn, Verena Kaynig, James Tompkin, Jeff W. Lichtman, Hanspeter Pfister:
Guided Proofreading of Automatic Segmentations for Connectomics. CVPR 2018: 9319-9328 - 2017
- [c5]Felix Gonda, Verena Kaynig, Thouis R. Jones, Daniel Haehn, Jeff W. Lichtman, Toufiq Parag, Hanspeter Pfister:
ICON: An interactive approach to train deep neural networks for segmentation of neuronal structures. ISBI 2017: 327-331 - [c4]Brian Matejek, Daniel Haehn, Fritz Lekschas, Michael Mitzenmacher, Hanspeter Pfister:
Compresso: Efficient Compression of Segmentation Data for Connectomics. MICCAI (1) 2017: 781-788 - [c3]Rudolph Pienaar, Ata Turk, Jorge L. Bernal-Rusiel, Nicolas Rannou, Daniel Haehn, Patricia Ellen Grant, Orran Krieger:
CHIPS - A Service for Collecting, Organizing, Processing, and Sharing Medical Image Data in the Cloud. DMAH@VLDB 2017: 29-35 - 2015
- [c2]Rudolph Pienaar, Nicolas Rannou, Jorge Bernal, Daniel Haehn, Patricia Ellen Grant:
ChRIS- A web-based neuroimaging and informatics system for collecting, organizing, processing, visualizing and sharing of medical data. EMBC 2015: 206-209 - 2013
- [c1]Daniel Haehn:
Slice: drop: collaborative medical imaging in the browser. SIGGRAPH Computer Animation Festival 2013: 104:1
Informal and Other Publications
- 2023
- [i9]Daniel Karl I. Weidele, Shazia Afzal, Abel N. Valente, Cole Makuch, Owen Cornec, Long Vu, Dharmashankar Subramanian, Werner Geyer, Rahul Nair, Inge Vejsbjerg, Radu Marinescu, Paulito P. Palmes, Elizabeth M. Daly, Loraine Franke, Daniel Haehn:
AutoDOViz: Human-Centered Automation for Decision Optimization. CoRR abs/2302.09688 (2023) - [i8]Loraine Franke, Tae Young Park, Jie Luo, Yogesh Rathi, Steve Pieper, Lipeng Ning, Daniel Haehn:
SlicerTMS: Interactive Real-time Visualization of Transcranial Magnetic Stimulation using Augmented Reality and Deep Learning. CoRR abs/2305.06459 (2023) - [i7]Kristin Qi, Jiali Cheng, Daniel Haehn:
Lesion Search with Self-supervised Learning. CoRR abs/2311.11014 (2023) - 2020
- [i6]Daniel Haehn, Loraine Franke, Fan Zhang, Suheyla Cetin Karayumak, Steve Pieper, Lauren O'Donnell, Yogesh Rathi:
TRAKO: Efficient Transmission of Tractography Data for Visualization. CoRR abs/2004.13630 (2020) - [i5]Loraine Franke, Daniel Karl I. Weidele, Fan Zhang, Suheyla Cetin Karayumak, Steve Pieper, Lauren J. O'Donnell, Yogesh Rathi, Daniel Haehn:
FiberStars: Visual Comparison of Diffusion Tractography Data between Multiple Subjects. CoRR abs/2005.08090 (2020) - 2018
- [i4]Vincent Casser, Kai Kang, Hanspeter Pfister, Daniel Haehn:
Fast Mitochondria Segmentation for Connectomics. CoRR abs/1812.06024 (2018) - 2017
- [i3]Daniel Haehn, Verena Kaynig, James Tompkin, Jeff W. Lichtman, Hanspeter Pfister:
Guided Proofreading of Automatic Segmentations for Connectomics. CoRR abs/1704.00848 (2017) - [i2]Rudolph Pienaar, Ata Turk, Jorge L. Bernal-Rusiel, Nicolas Rannou, Daniel Haehn, Patricia Ellen Grant, Orran Krieger:
CHIPS: A Service for Collecting, Organizing, Processing, and Sharing Medical Image Data in the Cloud. CoRR abs/1710.00734 (2017) - 2016
- [i1]Felix Gonda, Verena Kaynig, Thouis Ray Jones, Daniel Haehn, Jeff Lichtman, Toufiq Parag, Hanspeter Pfister:
Icon: An Interactive Approach to Train Deep Neural Networks for Segmentation of Neuronal Structures. CoRR abs/1610.09032 (2016)
Coauthor Index
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