Tammy Riklin Raviv, PhD

[Tammy Riklin Raviv photo]

Not too Short Bio and Research Statement
Since November 2012 I am a faculty member at the Electrical and Computer Engineering Department of Ben Gurion University.
My research primarily focuses on the development of mathematical and algorithmic tools for processing, analysis and understanding of natural, biological and medical images.
I `grew up' in a `pure' computer vision environment ( MSc, Computer Science, The Hebrew University of Jerusalem with Amnon Shashua ) and was gradually exposed to images that were not acquired by digital cameras (PhD, Electrical Engineering, Tel-Aviv University, with Nir Sochen and Nahum Kiryati ). So, it was just before my postdoc ( MIT , CSAIL with Polina Golland ; Harvard Medical School, PNL and the Imaging Platform of the Broad Institute of MIT and Harvrd ) where I became fascinated by the field of Biomedical Image Analysis. Not only do I find that addressing real world problems by providing feasible, reliable and efficient solutions is intriguing and challenging, but in many cases it gives a glimpse into a diversity of interesting scientific issues from other disciplines. Don't get me wrong, I am still a great Computer Vision advocate and do have a bunch of works addressing classical problems in object recognition, varying illumination, multiple-view geometry, abnormal motion detection, image registration and segmentation which I'm quite proud of. Yet, my current bread and butter (research projects) include object detection, segmentation, atlas construction and shape analysis in high throughput microscopy and Magnetic Resonance Imaging (MRI) with a particular emphasis on brain imaging.

I am currently establishing the BioMedical Image Computing (BioMic) laboratory. Excellent students who look for the match points between Computer Science and Engineering, Medicine and Biology through the eyes of modern imaging are welcomed to chat about the opportunities in my group.

Contact
[Email]
Location: BGU campus,Building 33, Office 212
Phone:+972-8-6428812
Fax: +972-8-6472949
Address: P.O.Box. 653, Beer-Sheva, 84105, ISRAEL

Curriculum Vitae

Coming Soon!!
The Third Interactive Medical Image Computing (IMIC) workshop , In conjunction with MICCAI, October 2016, Athens, Greece
IEEE International Symposium on Biomedical Imaging (ISBI), April 2017, Melbourne, Australia


Teaching
Deep Learning and Its Applications to Signal and Image Processing and Analysis
Introduction to Biomedical Imaging
Magnetic Resonance Imaging
Introduction to Computational Methods

Publications
[Publication]
Journal Papers

T. Hershkovich, T. Shalmon, O. Shitrit, N. Halay, B. Menze, I. Dolgopyat, I. Kahn, I. Shelef and T. Riklin Raviv,
A probabilistic model for 3D interactive segmentation,

Computer Vision and Image Understanding (CVIU), Special Issue on Probabilistic Models for Biomedical Image Analysis, Accepted, 2016.

B. Menze, K. Van Leemput, D. Lashkari, T. Riklin-Raviv, E. Geremia, E. Albert, et al. A generative probabilistic model and discriminative extensions for brain lesion segmentation with application to tumor and stroke,
IEEE Transaction on Medical Imaging, online publication, 2015.

B. Menze, A. Jakaby, S. Bauery, J. Kalpathy-Cramery, K. Farahaniy, J. Kirbyy, et al, (including T. Riklin Raviv), The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS),
IEEE Transaction on Medical Imaging, Vol. 34(10), pp. 1993-- 2024, Oct. 2015.

T. Riklin-Raviv, Yi Gao, James J. Levitt and S. Bouix Statistical Shape Analysis of Neuroanatomical Structures via Level-set based Shape Morphing.
SIAM Journal on Imaging Sciences, Vol. 7(3), pp. 1645--1668, November 2014.

Y. Gao, T. Riklin-Raviv, and S. Bouix, Shape analysis, a field in need of careful validation,
Human Brain Mapping, Vol. 35 (10), pp. 4965-4978, October 2014.

E. Dittrich, T. Riklin-Raviv, G. Kasprian, P. Brugger, D. Prayer and G. Langs A spatio-temporal latent atlas for semi-supervised learning of fetal brain segmentations and morphological age estimation.
Medical Image Analysis, Vol. 18(1), pp 9-21, Jan. 2014.

C. W"ahlby, L. Kamentsky , Z. H. Liu , T. Riklin-Raviv, A. L. Conery , E. J. ORourke, K. L. Sokolnicki , O. Visvikis , V. Ljosa , J. E. Irazoqui , P. Golland, G. Ruvkun, F. M. Ausubel and A. E. Carpenter An Image Analysis Toolbox for High-throughput C. Elegans Assays.
NATURE METHODS vol. 9 pp 627-763, July 2012.

T. Riklin Raviv, K. Van-Leemput, B. Menze, W.M. Wells III and P. Golland Segmentation of Image Ensambles via Latent Atlases.
Special Issue on the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2009. Medical Image Analysis (MedIA), Vol. 14(5) pp 654-665, October 2010.

T. Riklin Raviv, N. Sochen and N. Kiryati On Symmetry, Perspectivity and Level-set based Segmentation.
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 31(8) pp 1458--1471, August 2009

T. Riklin Raviv, N. Sochen and N. Kiryati Shape-based Mutual Segmentation.
International Journal of Computer Vision (IJCV), 79(3) pp 231--245, September 2008

T. Riklin Raviv, N. Kiryati and N. Sochen Prior-based Segmentation and Shape Registration in the Presence of Projective Distortion.
International Journal of Computer Vision (IJCV), 72(3), pp 309--328, May 2007

A. Shashua and T. Riklin Raviv The Quotient Image: Class Based Re-rendering and Recognition with Varying Illuminations.
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. 23(2), pp. 129--139, February 2001

Peer Reviewed Conference Papers

A. Benou, R. Veksler, A. Freidman and T. Riklin Raviv, De-noising of Contrast-Enhanced MRI Sequences by an Ensemble of Expert Deep Neural Networks,
MICCAI workshop on Deep Learning in Medical Image Analysis (DLMIA), Accepted, October 2016.

S. Gordon, I. Dolgopyat, I. Kahn and T. Riklin Raviv, Co-segmentation of Multiple Images into Multiple Regions: Application to Mouse Brain MRI,
IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), pages 399-402, April 2016.

A. Arbelle, N. Drayman, M. Bray, U. Alon, A. Carpenter and T. Riklin Raviv
Analysis of High-throughput Microscopy Videos: Catching Up with Cell Dynamics.

International Conference of Medical Image computing and Computer Assisted Intervention (MICCAI), pages 218--225, October 2015

T. Gilad, M.A. Bray, A.E. Carpenter and T. Riklin Raviv Symmetry based mitosis detection in time-lapse microscopy.
IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), pages 164--167, April 2015

O. Shitrit, T. Hershkovitch, T. Shalmon, I. Shelef and T. Riklin Raviv Probabilistic Model for 3D Interactive Segmentation.
MICCAI workshop on Interactive Medical Image Computing (IMIC), September, 2014

T. Riklin-Raviv, Y. Gao, J. Levitt and S. Bouix Statistical Shape Analysis for Population Studies via Level-set based Shape Morphing.
ECCV workshop on Non-Rigid Shape Analysis and Deformable Image Alignment (NORDIA), October, 2012

T. Riklin Raviv, K. Van-Leemput and B.M. Menze Multi-modal brain tumor segmentation via latent atlases.
MICCAI challenge on Multimodal Brain Tumor Segmentation, pp. 64--73, October 2012

E. Dittrich, T. Riklin-Raviv, G. Kasprian, P. Brugger, D. Prayer and G. Langs Learning a Spatio-temporal Latent Atlas for Fetal Brain Segmentation.
MICCAI workshop: Image Analysis of Human Brain Development, September 2011

T. Riklin-Raviv, V. Ljosa, A. L. Conery, F. M. Ausubel, A.E. Carpenter, P. Golland and C. W"ahlby Morphology-Guided Graph Search for Untangling Objects: C. Elegans Analysis
International Conference of Medical Image computing and Computer Assisted Intervention (MICCAI), pp. 634-641, September 2010

C. W"ahlby, T. Riklin-Raviv, V. Ljosa, A. L. Conery, P. Golland, F. M. Ausubel and A. E. Carpenter Resolving Clustered Worms via Probabilistic Shape Models
IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), April 2010

T. Riklin Raviv, K. Van-Leemput, W.M. Wells III and P. Golland Joint Segmentation of Image Ensambles via Latent Atlases.
International Conference of Medical Image computing and Computer Assisted Intervention (MICCAI), Part I, LNCS 5761, pp 272--280, September 2009. Received the MICCAI-09 Young Scientist Award.

T. Riklin Raviv, B.M. Menze, K. Van-Leemput, B. Stieltjes, M.A. Weber, N. Ayache, W.M. Wells III and P. Golland Joint Segmentation via Patient-Specific Latent Anatomy Model.
MICCAI workshop: Probabilistic Models for Medical Imaging Analysis (PMMIA), September 2009

N. Ben-Zadok, T. Riklin Raviv and N. Kiryati Interactive Level Set Segmentation for Image-guided Therapy
IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), pp 1079--1082, June 2009

N. Kiryati, T. Riklin Raviv, Y. Ivanchenko, S. Rochel Real-time Abnormal Motion Detection in Surveillance Video.
International Conference on Pattern Recognition (ICPR), December 2008

T. Riklin Raviv, N. Kiryati, N. Sochen, N. Ben-Zadok, S. Gefen, L. Bertand and J. Nissanov Propagating Distributions for Segmentation of Brain Atlas.
IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), pp 1304--1307, April 2007

T. Riklin Raviv, N. Kiryati and N. Sochen Segmentation by Level sets and Symmetry.

IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pp 1015--1022, New York, June 2006

T. Riklin Raviv, N. Sochen and N. Kiryati Mutual Segmentation with Level Sets.
The 5th IEEE Workshop on Perceptual Organization in Computer Vision, in conjunction with the CVPR, New York, June 2006

T. Riklin Raviv, N. Kiryati and N. Sochen Prior-based Segmentation by Projective Registration and Level sets.
IEEE International Conf. on Computer Vision (ICCV), pp 204--211, October 2005.

T. Riklin Raviv, N. Kiryati and N. Sochen Unlevel-Set: Geometry and Prior-based Segmentation.
Proc. of the European Conference on Computer Vision(ECCV), pp.50--61, May 2004

T. Riklin Raviv and A. Shashua The Quotient Image: Class Based Recognition and Synthesis with Varying Illumination Conditions.
IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pp.566-571, June 1999

Short papers and abstracts

J. Levitt, Y. Rathi, T. Riklin Raviv, P. G. Nestor, L. Levin, R.W. McCarley and M.E. Shenton, Frontrostriatal dysconnectivity in Schizophrenia
In Schizophrenia bulletin. Vol. 41, pp. 263-263, 2015.

J. Levitt, Y. Rathi, T. Riklin Raviv, R.W. McCarley and M.E. Shenton, DTI Connectivity-Based Parcellation of the Striatum in Schizophrenia.
Biological Psychiatry. Vol. 75, No. 9, pp. 375-375, 2014.

J. Levitt, Y. Rathi, T. Riklin Raviv, R. McCarley, M.E. Shenton, Connectivity-based Parcellation of the Striatum in Schizophrenia Using Diffusion Weighted Imaging (DWI). Neuropsychopharmacology. 39, 221-222, 2014.

T. Riklin Raviv Y. Gao, and S. Bouix Statistical shape analysis with modified Hausdorff distance.
IEEE Engineering in Medicine and Biology Society (EMBS), 2012.

Theses
T. Riklin Raviv Prior based Image Segmentation.

T. Riklin Raviv The Quotient Image: Class Based Re-rendering and Recognition With Varying Illuminations.

Patent
N. Kiryati, T. Riklin Raviv, Y. Ivanchenko, S. Rochel, Y. Dvir and D. Harari
Apparatus and Methods for the Detection of Abnormal Motion in a Video Stream.
European Patent EP1631073B1

Research

Segmentation of Image Ensembles Via Latent Atlases
Interactive Level-set Segmentation for Image-guided Therapy
Propageting Distributions for Segmentation of Mouse Brain Atlas
Geometry and Prior Based Segmentation with Level-sets
Real-time Abnormal Motion Detection in Surveillance Video
The Quotient Image: Class based Recognition and Synthesis under Varying Illumination Conditions


Impact/Links/Collaborations
C. elegans Analysis
Image analysis for high-throughput C. elegans infection and metabolism assays, NIH, RO1, Sample Application
Segmentation of Image Ensembles Via Latent Atlases
Young Scientist Award, Miccai 2009
A glimpse to google scholar


Presentations
Statistical Shape Analysis for Population Studies via Level-set Based Shape Morphing
Segmentation of Image Ensembles Via Latent Atlases
Shape-based Segmentation with Level-sets
Real-time Abnormal Motion Detection in Surveillance Video
The Quotient Image:Class based Recognition and Synthesis under Varying Illumination Conditions

Teaching
Introduction to Systems Programming, 2003-2006
Digital Logic Systems 2004-2007
The MVP Seminar 2006-2007

Best Ever Projects