Daniel Haehn

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 33

Top Topics

Automatic Segmentation

Interactive Visual

Complexity Analysis

Top Venues

IEEE Trans. Vis. Comput. Graph.

Publications

Sanghyuk Kim, Edward Gaibor, Daniel Haehn
Web-based Melanoma Detection. CoRR (2024)
Edward Gaibor, Shruti Varade, Rohini Deshmukh, Tim Meyer, Mahsa Geshvadi, Sanghyuk Kim, Vidhya Sree Narayanappa, Daniel Haehn
Boostlet.js: Image processing plugins for the web via JavaScript injection. CoRR (2024)
Tim Meyer, Gabi Dreo Rodosek, Daniel Haehn
WebGL-based Image Processing through JavaScript Injection. Web3D (2024)
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) (2023)
Kristin Qi, Jiali Cheng, Daniel Haehn
Lesion Search with Self-supervised Learning. CoRR (2023)
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 (2023)
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)
Kristin Qi, Jiali Cheng, Daniel Haehn
Lesion Search with Self-supervised Learning. Tiny Papers @ ICLR (2023)
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 (2023)
Neha Goyal, Yahiya Hussain, Gianna G. Yang, Daniel Haehn
Real-Time Alignment for Connectomics. WBIR (2022)
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)
Nalini M. Singh, Jordan B. Harrod, Sandya Subramanian, Mitchell Robinson, Ken Chang, Suheyla Cetin Karayumak, Adrian Vasile Dalca, Simon 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) (2022)
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)
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)
Vincent Casser, Kai Kang, Hanspeter Pfister, Daniel Haehn
Fast Mitochondria Detection for Connectomics. MIDL (2020)
Loraine Franke, Daniel Haehn
Modern Scientific Visualizations on the Web. Informatics 7 (4) (2020)
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 (2020)
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) (2020)
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 (2020)
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)
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)
Daniel Haehn, James Tompkin, Hanspeter Pfister
Evaluating 'Graphical Perception' with CNNs. IEEE Trans. Vis. Comput. Graph. 25 (1) (2019)
Brian Matejek, Daniel Haehn, Haidong Zhu, Donglai Wei, Toufiq Parag, Hanspeter Pfister
Biologically-Constrained Graphs for Global Connectomics Reconstruction. CVPR (2019)
Daniel Haehn, Verena Kaynig, James Tompkin, Jeff W. Lichtman, Hanspeter Pfister
Guided Proofreading of Automatic Segmentations for Connectomics. CVPR (2018)
Vincent Casser, Kai Kang, Hanspeter Pfister, Daniel Haehn
Fast Mitochondria Segmentation for Connectomics. CoRR (2018)
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 (2017)
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)
Daniel Haehn, Verena Kaynig, James Tompkin, Jeff W. Lichtman, Hanspeter Pfister
Guided Proofreading of Automatic Segmentations for Connectomics. CoRR (2017)
Brian Matejek, Daniel Haehn, Fritz Lekschas, Michael Mitzenmacher, Hanspeter Pfister
Compresso: Efficient Compression of Segmentation Data for Connectomics. MICCAI (1) (2017)
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) (2017)
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)
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) (2016)
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 (2016)
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)
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) (2014)
Daniel Haehn
Slice: drop: collaborative medical imaging in the browser. SIGGRAPH Computer Animation Festival (2013)