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ORCIDTammy Riklin-Raviv
Person information
- affiliation: Ben Gurion University of the Negev, Israel
- affiliation (former): MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, USA
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2020 – today
- 2024
[i12]Daniel Duenias, Brennan Nichyporuk, Tal Arbel, Tammy Riklin Raviv:
HyperFusion: A Hypernetwork Approach to Multimodal Integration of Tabular and Medical Imaging Data for Predictive Modeling. CoRR abs/2403.13319 (2024)- 2023
- [j20]Mor Avi-Aharon
, Assaf Arbelle, Tammy Riklin Raviv:
Differentiable Histogram Loss Functions for Intensity-based Image-to-Image Translation. IEEE Trans. Pattern Anal. Mach. Intell. 45(10): 11642-11653 (2023) - [c29]Itay Buchnik, Or Berebi, Tammy Riklin Raviv, Nir Shlezinger:
Generating Artistic Images Via Few-Shot Style Transfer. ICASSP Workshops 2023: 1-5 - 2022
- [j19]Assaf Arbelle, Shaked Cohen, Tammy Riklin Raviv:
Dual-Task ConvLSTM-UNet for Instance Segmentation of Weakly Annotated Microscopy Videos. IEEE Trans. Medical Imaging 41(8): 1948-1960 (2022) - [c28]Tal Ben-Haim, Tammy Riklin Raviv:
Graph Neural Network for Cell Tracking in Microscopy Videos. ECCV (21) 2022: 610-626 - [c27]Tal Ben-Haim, Ron Moshe Sofer, Gal Ben-Arie, Ilan Shelef, Tammy Riklin Raviv:
A Deep Ensemble Learning Approach to Lung CT Segmentation for Covid-19 Severity Assessment. ICIP 2022: 151-155 - [i11]Tal Ben-Haim, Tammy Riklin-Raviv:
Graph Neural Network for Cell Tracking in Microscopy Videos. CoRR abs/2202.04731 (2022) - [i10]Tal Ben-Haim, Ron Moshe Sofer, Gal Ben-Arie, Ilan Shelef, Tammy Riklin-Raviv:
A Deep Ensemble Learning Approach to Lung CT Segmentation for COVID-19 Severity Assessment. CoRR abs/2207.02322 (2022) - 2021
- [j18]Yael Ziv, Jacob Goldberger, Tammy Riklin Raviv:
Stochastic weight pruning and the role of regularization in shaping network structure. Neurocomputing 462: 555-567 (2021) - [j17]Shiri Gordon, Boris Kodner, Tal Goldfryd, Michael Sidorov, Jacob Goldberger, Tammy Riklin Raviv:
An atlas of classifiers - a machine learning paradigm for brain MRI segmentation. Medical Biol. Eng. Comput. 59(9): 1833-1849 (2021) - [c26]Tal Goldfryd, Shiri Gordon, Tammy Riklin Raviv:
Deep Semi-Supervised Bias Field Correction Of Mr Images. ISBI 2021: 1836-1840 - [d1]Assaf Arbelle, Shaked Cohen, Tammy Riklin Raviv:
BGUSIM. IEEE DataPort, 2021
- 2020
- [j16]Roy Shaul, Itamar David, Ohad Shitrit, Tammy Riklin Raviv:
Subsampled brain MRI reconstruction by generative adversarial neural networks. Medical Image Anal. 65: 101747 (2020) - [i9]Mor Avi-Aharon, Assaf Arbelle, Tammy Riklin Raviv:
DeepHist: Differentiable Joint and Color Histogram Layers for Image-to-Image Translation. CoRR abs/2005.03995 (2020) - [i8]Yael Ben-Guigui, Jacob Goldberger, Tammy Riklin-Raviv:
The Role of Regularization in Shaping Weight and Node Pruning Dependency and Dynamics. CoRR abs/2012.03827 (2020)
2010 – 2019
- 2019
- [j15]Topaz Gilad, José Reyes, Jia-Yun Chen, Galit Lahav, Tammy Riklin Raviv:
Fully unsupervised symmetry-based mitosis detection in time-lapse cell microscopy. Bioinform. 35(15): 2644-2653 (2019) - [j14]Itay Benou, Ronel Veksler, Alon Friedman, Tammy Riklin Raviv:
Combining white matter diffusion and geometry for tract-specific alignment and variability analysis. NeuroImage 200: 674-689 (2019) - [c25]Assaf Arbelle, Tammy Riklin Raviv:
Microscopy Cell Segmentation Via Convolutional LSTM Networks. ISBI 2019: 1008-1012 - [c24]Itay Benou, Tammy Riklin Raviv:
DeepTract: A Probabilistic Deep Learning Framework for White Matter Fiber Tractography. MICCAI (3) 2019: 626-635 - [i7]Assaf Arbelle, Eliav Elul, Tammy Riklin Raviv:
QANet - Quality Assurance Network for Microscopy Cell Segmentation. CoRR abs/1904.08503 (2019) - [i6]Or Shwartzman, Harel Gazit, Ilan Shelef, Tammy Riklin-Raviv:
The Impact of an Inter-rater Bias on Neural Network Training. CoRR abs/1906.11872 (2019) - [i5]Mor Avi-Aharon, Assaf Arbelle, Tammy Riklin Raviv:
Hue-Net: Intensity-based Image-to-Image Translation with Differentiable Histogram Loss Functions. CoRR abs/1912.06044 (2019) - 2018
- [j13]Assaf Arbelle, José Reyes, Jia-Yun Chen, Galit Lahav, Tammy Riklin Raviv:
A probabilistic approach to joint cell tracking and segmentation in high-throughput microscopy videos. Medical Image Anal. 47: 140-152 (2018) - [j12]Shiri Gordon, Irit Dolgopyat, Itamar Kahn, Tammy Riklin Raviv:
Multidimensional co-segmentation of longitudinal brain MRI ensembles in the presence of a neurodegenerative process. NeuroImage 178: 346-369 (2018) - [c23]O. A. Gorodissky, A. Sharon, A. Danov, Alon Friedman, Tammy Riklin Raviv:
Symmetry-Based Analysis of Diffusion MRI for the Detection of Brain Impairments. ICIP 2018: 376-379 - [c22]Heli Ben Hamu Goldberg, Jonathan Mushkin, Tammy Riklin Raviv, Nir A. Sochen:
Sampling Technique for Defining Segmentation Error Margins with Application to Structural Brain Mri. ICIP 2018: 734-738 - [c21]Assaf Arbelle, Tammy Riklin Raviv:
Microscopy cell segmentation via adversarial neural networks. ISBI 2018: 645-648 - [c20]Tsachi Hershkovich, Tammy Riklin-Raviv:
Model-dependent uncertainty estimation of medical image segmentation. ISBI 2018: 1373-1376 - [i4]Assaf Arbelle, Tammy Riklin Raviv:
Microscopy Cell Segmentation via Convolutional LSTM Networks. CoRR abs/1805.11247 (2018) - [i3]Itay Benou, Tammy Riklin-Raviv:
DeepTract: A Probabilistic Deep Learning Framework for White Matter Fiber Tractography. CoRR abs/1812.05129 (2018) - 2017
- [j11]Ariel Benou, Ronel Veksler, Alon Friedman, Tammy Riklin-Raviv:
Ensemble of expert deep neural networks for spatio-temporal denoising of contrast-enhanced MRI sequences. Medical Image Anal. 42: 145-159 (2017) - [c19]Ohad Shitrit, Tammy Riklin Raviv:
Accelerated Magnetic Resonance Imaging by Adversarial Neural Network. DLMIA/ML-CDS@MICCAI 2017: 30-38 - [c18]Boris Kodner, Shiri Gordon, Jacob Goldberger, Tammy Riklin Raviv:
Atlas of Classifiers for Brain MRI Segmentation. MLMI@MICCAI 2017: 36-44 - [c17]Tammy Riklin Raviv:
Multinomial Level-Set Framework for Multi-region Image Segmentation. SSVM 2017: 386-395 - [i2]Assaf Arbelle, Tammy Riklin Raviv:
Microscopy Cell Segmentation via Adversarial Neural Networks. CoRR abs/1709.05860 (2017) - [i1]Itay Benou, Ronel Veksler, Alon Friedman, Tammy Riklin Raviv:
Fiber-Flux Diffusion Density for White Matter Tracts Analysis: Application to Mild Anomalies Localization in Contact Sports Players. CoRR abs/1709.06122 (2017) - 2016
- [j10]Tsachi Hershkovich, Tamar Shalmon, Ohad Shitrit, Nir Halay, Bjoern H. Menze, Irit Dolgopyat, Itamar Kahn, Ilan Shelef, Tammy Riklin Raviv:
Probabilistic model for 3D interactive segmentation. Comput. Vis. Image Underst. 151: 47-60 (2016) - [j9]Bjoern H. Menze, Koen Van Leemput, Danial Lashkari, Tammy Riklin-Raviv, Ezequiel Geremia, Esther Alberts, Philipp Gruber, Susanne Wegener, Marc-André Weber, Gábor Székely, Nicholas Ayache, Polina Golland:
A Generative Probabilistic Model and Discriminative Extensions for Brain Lesion Segmentation - With Application to Tumor and Stroke. IEEE Trans. Medical Imaging 35(4): 933-946 (2016) - [c16]Shiri Gordon, Irit Dolgopyat, Itamar Kahn, Tammy Riklin Raviv:
Co-segmentation of multiple images into multiple regions: Application to mouse brain MRI. ISBI 2016: 399-402 - [c15]Ariel Benou, Ronel Veksler, Alon Friedman, Tammy Riklin Raviv:
De-noising of Contrast-Enhanced MRI Sequences by an Ensemble of Expert Deep Neural Networks. LABELS/DLMIA@MICCAI 2016: 95-110 - 2015
- [j8]Bjoern H. Menze, András Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Keyvan Farahani, Justin S. Kirby, Yuliya Burren, Nicole Porz, Johannes Slotboom, Roland Wiest, Levente Lanczi, Elizabeth R. Gerstner, Marc-André Weber, Tal Arbel, Brian B. Avants, Nicholas Ayache, Patricia Buendia, D. Louis Collins, Nicolas Cordier, Jason J. Corso, Antonio Criminisi, Tilak Das, Herve Delingette, Çagatay Demiralp, Christopher R. Durst, Michel Dojat, Senan Doyle, Joana Festa, Florence Forbes, Ezequiel Geremia, Ben Glocker, Polina Golland, Xiaotao Guo, Andac Hamamci, Khan M. Iftekharuddin, Raj Jena, Nigel M. John, Ender Konukoglu, Danial Lashkari, José Antonio Mariz, Raphael Meier, Sérgio Pereira, Doina Precup, Stephen J. Price, Tammy Riklin Raviv, Syed M. S. Reza, Michael T. Ryan, Duygu Sarikaya, Lawrence H. Schwartz, Hoo-Chang Shin, Jamie Shotton, Carlos A. Silva, Nuno J. Sousa, Nagesh K. Subbanna, Gábor Székely, Thomas J. Taylor, Owen M. Thomas, Nicholas J. Tustison, Gözde B. Ünal, Flor Vasseur, Max Wintermark, Dong Hye Ye, Liang Zhao, Binsheng Zhao, Darko Zikic, Marcel Prastawa, Mauricio Reyes, Koen Van Leemput:
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS). IEEE Trans. Medical Imaging 34(10): 1993-2024 (2015) - [c14]Topaz Gilad, Mark-Anthony Bray, Anne E. Carpenter, Tammy Riklin Raviv:
Symmetry-based mitosis detection in time-lapse microscopy. ISBI 2015: 164-167 - [c13]Assaf Arbelle, N. Drayman, Mark-Anthony Bray, U. Alon, Anne E. Carpenter, Tammy Riklin Raviv:
Analysis of High-throughput Microscopy Videos: Catching Up with Cell Dynamics. MICCAI (3) 2015: 218-225 - 2014
- [j7]Eva Dittrich, Tammy Riklin Raviv, Gregor Kasprian, René Donner, Peter C. Brugger, Daniela Prayer, Georg Langs:
A spatio-temporal latent atlas for semi-supervised learning of fetal brain segmentations and morphological age estimation. Medical Image Anal. 18(1): 9-21 (2014) - [j6]Tammy Riklin Raviv, Yi Gao, James J. Levitt, Sylvain Bouix:
Statistical Shape Analysis of Neuroanatomical Structures via Level-Set-based Shape Morphing. SIAM J. Imaging Sci. 7(3): 1645-1668 (2014) - 2012
- [c12]Tammy Riklin Raviv, Yi Gao, James J. Levitt, Sylvain Bouix:
Statistical Shape Analysis for Population Studies via Level-Set Based Shape Morphing. ECCV Workshops (1) 2012: 42-51 - 2010
- [j5]Tammy Riklin-Raviv, Koen Van Leemput, Bjoern H. Menze, William M. Wells III, Polina Golland:
Segmentation of image ensembles via latent atlases. Medical Image Anal. 14(5): 654-665 (2010) - [c11]Carolina Wählby, Tammy Riklin-Raviv, Vebjorn Ljosa, Annie L. Conery, Polina Golland, Frederick M. Ausubel, Anne E. Carpenter:
Resolving clustered worms via probabilistic shape models. ISBI 2010: 552-555 - [c10]Tammy Riklin Raviv, Vebjorn Ljosa, Annie L. Conery, Frederick M. Ausubel, Anne E. Carpenter, Polina Golland, Carolina Wählby:
Morphology-Guided Graph Search for Untangling Objects: C. elegans Analysis. MICCAI (3) 2010: 634-641
2000 – 2009
- 2009
- [j4]Tammy Riklin-Raviv, Nir A. Sochen, Nahum Kiryati:
On Symmetry, Perspectivity, and Level-Set-Based Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 31(8): 1458-1471 (2009) - [c9]Nir Ben-Zadok, Tammy Riklin Raviv, Nahum Kiryati:
Interactive Level Set Segmentation for Image-Guided Therapy. ISBI 2009: 1079-1082 - [c8]Tammy Riklin Raviv, Koen Van Leemput, William M. Wells III, Polina Golland:
Joint Segmentation of Image Ensembles via Latent Atlases. MICCAI (1) 2009: 272-280 - 2008
- [j3]Tammy Riklin-Raviv, Nir A. Sochen, Nahum Kiryati:
Shape-Based Mutual Segmentation. Int. J. Comput. Vis. 79(3): 231-245 (2008) - [c7]Nahum Kiryati, Tammy Riklin-Raviv, Yan Ivanchenko, Shay Rochel:
Real-time abnormal motion detection in surveillance video. ICPR 2008: 1-4 - 2007
- [j2]Tammy Riklin-Raviv, Nahum Kiryati, Nir A. Sochen:
Prior-based Segmentation and Shape Registration in the Presence of Perspective Distortion. Int. J. Comput. Vis. 72(3): 309-328 (2007) - [c6]Tammy Riklin-Raviv, Nir A. Sochen, Nahum Kiryati, Nir Ben-Zadok, Smadar Gefen, Louise Bertrand, Jonathan Nissanov:
Propagating Distributions for Segmentation of Brain Atlas. ISBI 2007: 1304-1307 - 2006
- [c5]Tammy Riklin-Raviv, Nir A. Sochen, Nahum Kiryati:
Mutual Segmentation with Level Sets. CVPR Workshops 2006: 177 - [c4]Tammy Riklin-Raviv, Nahum Kiryati, Nir A. Sochen:
Segmentation by Level Sets and Symmetry. CVPR (1) 2006: 1015-1022 - 2005
- [c3]Tammy Riklin-Raviv, Nahum Kiryati, Nir A. Sochen:
Prior-Based Segmentation by Projective Registration and Level Sets. ICCV 2005: 204-211 - 2004
- [c2]Tammy Riklin-Raviv, Nahum Kiryati, Nir A. Sochen:
Unlevel-Sets: Geometry and Prior-Based Segmentation. ECCV (4) 2004: 50-61 - 2001
- [j1]Amnon Shashua, Tammy Riklin-Raviv:
The Quotient Image: Class-Based Re-Rendering and Recognition with Varying Illuminations. IEEE Trans. Pattern Anal. Mach. Intell. 23(2): 129-139 (2001)
1990 – 1999
- 1999
- [c1]Tammy Riklin-Raviv, Amnon Shashua:
The Quotient Image: Class Based Recognition and Synthesis under Varying Illumination Conditions. CVPR 1999: 2566-
Coauthor Index
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