Zobrazeno 1 - 10
of 62
pro vyhledávání: '"Haehn, Daniel"'
Autor:
Gaibor, Edward, Varade, Shruti, Deshmukh, Rohini, Meyer, Tim, Geshvadi, Mahsa, Kim, SangHyuk, Narayanappa, Vidhya Sree, Haehn, Daniel
Can web-based image processing and visualization tools easily integrate into existing websites without significant time and effort? Our Boostlet.js library addresses this challenge by providing an open-source, JavaScript-based web framework to enable
Externí odkaz:
http://arxiv.org/abs/2405.07868
Melanoma is the most aggressive form of skin cancer, and early detection can significantly increase survival rates and prevent cancer spread. However, developing reliable automated detection techniques is difficult due to the lack of standardized dat
Externí odkaz:
http://arxiv.org/abs/2403.14898
Content-based image retrieval (CBIR) with self-supervised learning (SSL) accelerates clinicians' interpretation of similar images without manual annotations. We develop a CBIR from the contrastive learning SimCLR and incorporate a generalized-mean (G
Externí odkaz:
http://arxiv.org/abs/2311.11014
Autor:
Li, Jianning, Zhou, Zongwei, Yang, Jiancheng, Pepe, Antonio, Gsaxner, Christina, Luijten, Gijs, Qu, Chongyu, Zhang, Tiezheng, Chen, Xiaoxi, Li, Wenxuan, Wodzinski, Marek, Friedrich, Paul, Xie, Kangxian, Jin, Yuan, Ambigapathy, Narmada, Nasca, Enrico, Solak, Naida, Melito, Gian Marco, Vu, Viet Duc, Memon, Afaque R., Schlachta, Christopher, De Ribaupierre, Sandrine, Patel, Rajnikant, Eagleson, Roy, Chen, Xiaojun, Mächler, Heinrich, Kirschke, Jan Stefan, de la Rosa, Ezequiel, Christ, Patrick Ferdinand, Li, Hongwei Bran, Ellis, David G., Aizenberg, Michele R., Gatidis, Sergios, Küstner, Thomas, Shusharina, Nadya, Heller, Nicholas, Andrearczyk, Vincent, Depeursinge, Adrien, Hatt, Mathieu, Sekuboyina, Anjany, Löffler, Maximilian, Liebl, Hans, Dorent, Reuben, Vercauteren, Tom, Shapey, Jonathan, Kujawa, Aaron, Cornelissen, Stefan, Langenhuizen, Patrick, Ben-Hamadou, Achraf, Rekik, Ahmed, Pujades, Sergi, Boyer, Edmond, Bolelli, Federico, Grana, Costantino, Lumetti, Luca, Salehi, Hamidreza, Ma, Jun, Zhang, Yao, Gharleghi, Ramtin, Beier, Susann, Sowmya, Arcot, Garza-Villarreal, Eduardo A., Balducci, Thania, Angeles-Valdez, Diego, Souza, Roberto, Rittner, Leticia, Frayne, Richard, Ji, Yuanfeng, Ferrari, Vincenzo, Chatterjee, Soumick, Dubost, Florian, Schreiber, Stefanie, Mattern, Hendrik, Speck, Oliver, Haehn, Daniel, John, Christoph, Nürnberger, Andreas, Pedrosa, João, Ferreira, Carlos, Aresta, Guilherme, Cunha, António, Campilho, Aurélio, Suter, Yannick, Garcia, Jose, Lalande, Alain, Vandenbossche, Vicky, Van Oevelen, Aline, Duquesne, Kate, Mekhzoum, Hamza, Vandemeulebroucke, Jef, Audenaert, Emmanuel, Krebs, Claudia, van Leeuwen, Timo, Vereecke, Evie, Heidemeyer, Hauke, Röhrig, Rainer, Hölzle, Frank, Badeli, Vahid, Krieger, Kathrin, Gunzer, Matthias, Chen, Jianxu, van Meegdenburg, Timo, Dada, Amin, Balzer, Miriam, Fragemann, Jana, Jonske, Frederic, Rempe, Moritz, Malorodov, Stanislav, Bahnsen, Fin H., Seibold, Constantin, Jaus, Alexander, Marinov, Zdravko, Jaeger, Paul F., Stiefelhagen, Rainer, Santos, Ana Sofia, Lindo, Mariana, Ferreira, André, Alves, Victor, Kamp, Michael, Abourayya, Amr, Nensa, Felix, Hörst, Fabian, Brehmer, Alexander, Heine, Lukas, Hanusrichter, Yannik, Weßling, Martin, Dudda, Marcel, Podleska, Lars E., Fink, Matthias A., Keyl, Julius, Tserpes, Konstantinos, Kim, Moon-Sung, Elhabian, Shireen, Lamecker, Hans, Zukić, Dženan, Paniagua, Beatriz, Wachinger, Christian, Urschler, Martin, Duong, Luc, Wasserthal, Jakob, Hoyer, Peter F., Basu, Oliver, Maal, Thomas, Witjes, Max J. H., Schiele, Gregor, Chang, Ti-chiun, Ahmadi, Seyed-Ahmad, Luo, Ping, Menze, Bjoern, Reyes, Mauricio, Deserno, Thomas M., Davatzikos, Christos, Puladi, Behrus, Fua, Pascal, Yuille, Alan L., Kleesiek, Jens, Egger, Jan
Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit s
Externí odkaz:
http://arxiv.org/abs/2308.16139
Autor:
Franke, Loraine, Park, Tae Young, Luo, Jie, Rathi, Yogesh, Pieper, Steve, Ning, Lipeng, Haehn, Daniel
We present a real-time visualization system for Transcranial Magnetic Stimulation (TMS), a non-invasive neuromodulation technique for treating various brain disorders and mental health diseases. Our solution targets the current challenges of slow and
Externí odkaz:
http://arxiv.org/abs/2305.06459
Autor:
Weidele, Daniel Karl I., Afzal, Shazia, Valente, Abel N., Makuch, Cole, Cornec, Owen, Vu, Long, Subramanian, Dharmashankar, Geyer, Werner, Nair, Rahul, Vejsbjerg, Inge, Marinescu, Radu, Palmes, Paulito, Daly, Elizabeth M., Franke, Loraine, Haehn, Daniel
We present AutoDOViz, an interactive user interface for automated decision optimization (AutoDO) using reinforcement learning (RL). Decision optimization (DO) has classically being practiced by dedicated DO researchers where experts need to spend lon
Externí odkaz:
http://arxiv.org/abs/2302.09688
Autor:
Franke, Loraine, Weidele, Daniel Karl I., Zhang, Fan, Cetin-Karayumak, Suheyla, Pieper, Steve, O'Donnell, Lauren J., Rathi, Yogesh, Haehn, Daniel
Publikováno v:
2021 IEEE 14th Pacific Visualization Symposium (PacificVis)
Tractography from high-dimensional diffusion magnetic resonance imaging (dMRI) data allows brain's structural connectivity analysis. Recent dMRI studies aim to compare connectivity patterns across subject groups and disease populations to understand
Externí odkaz:
http://arxiv.org/abs/2005.08090
Autor:
Haehn, Daniel, Franke, Loraine, Zhang, Fan, Karayumak, Suheyla Cetin, Pieper, Steve, O'Donnell, Lauren, Rathi, Yogesh
Fiber tracking produces large tractography datasets that are tens of gigabytes in size consisting of millions of streamlines. Such vast amounts of data require formats that allow for efficient storage, transfer, and visualization. We present TRAKO, a
Externí odkaz:
http://arxiv.org/abs/2004.13630
High-resolution connectomics data allows for the identification of dysfunctional mitochondria which are linked to a variety of diseases such as autism or bipolar. However, manual analysis is not feasible since datasets can be petabytes in size. We pr
Externí odkaz:
http://arxiv.org/abs/1812.06024
Akademický článek
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