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Hedgehog Shape Priors for Multi-Object Segmentation

Hossam Isack, Olga Veksler, Milan Sonka, Yuri Boykov
2016 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
We propose a more general multi-object segmentation approach. Moreover, each object can be constrained by a more descriptive shape prior, "hedgehog".  ...  Star-convexity prior is popular for interactive single object segmentation due to its simplicity and amenability to binary graph cut optimization.  ...  Sue O'Dorisio and Yusuf Menda for providing the PET-CT liver data (NIH grant U01-CA140206). This work was also supported by NSERC Discovery and RTI grants (Canada) for Y. Boykov and O. Veksler.  ... 
doi:10.1109/cvpr.2016.267 dblp:conf/cvpr/IsackVSB16 fatcat:wh5dasbv4va2pnphakfho4ydqm

A-expansion for multiple "hedgehog" shapes [article]

Hossam Isack, Yuri Boykov, Olga Veksler
2016 arXiv   pre-print
This paper proposes an approach to multiobject segmentation where objects could be restricted to separate "hedgehog" shapes.  ...  We show that a-expansion moves are submodular for our multi-shape constraints.  ...  In this case, we interpolate the vector field's orientation for every neighboring pixels and eliminate their edge constraint(s) if it were not consistent with the interpolated orientation, as shown in  ... 
arXiv:1602.01006v1 fatcat:aqsgrteznzauxlqecdmqf4llga

K-convexity Shape Priors for Segmentation [chapter]

Hossam Isack, Lena Gorelick, Karin Ng, Olga Veksler, Yuri Boykov
2018 Lecture Notes in Computer Science  
For example, one approach segments an object via optimizing its k coverage by disjoint convex parts, which we show is highly sensitive to local minima.  ...  Our shape prior is useful in practice, e.g. biomedical applications, and its optimization is robust to local minima.  ...  Menda for providing the liver data NIH grant U01-CA140206. This work was also supported by NSERC Discovery and RTI grants (Canada) for Y. Boykov and O. Veksler.  ... 
doi:10.1007/978-3-030-01252-6_3 fatcat:327s7kwvfvgl3gxhhruyn2zjha

Efficient Optimization for Hierarchically-Structured Interacting Segments (HINTS)

Hossam Isack, Olga Veksler, Ipek Oguz, Milan Sonka, Yuri Boykov
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
We propose an effective optimization algorithm for a general hierarchical segmentation model with geometric interactions between segments.  ...  Generic a-expansion results in weak local minima, while common binary multi-layered formulations lead to nonsubmodularity, complex high-order potentials, or polar domain unwrapping and shape biases.  ...  Menda for providing the liver data (NIH grant U01-CA140206). This work was also supported by NSERC Discovery and RTI grants (Canada) for Y. Boykov and O. Veksler.  ... 
doi:10.1109/cvpr.2017.529 dblp:conf/cvpr/IsackVOSB17 fatcat:nngvkrgedjhqtfqs5vi226vsva

Efficient optimization for Hierarchically-structured Interacting Segments (HINTS) [article]

Hossam Isack, Olga Veksler, Ipek Oguz, Milan Sonka, Yuri Boykov
2017 arXiv   pre-print
We propose an effective optimization algorithm for a general hierarchical segmentation model with geometric interactions between segments.  ...  Generic -expansion results in weak local minima, while common binary multi-layered formulations lead to non-submodularity, complex high-order potentials, or polar domain unwrapping and shape biases.  ...  Furthermore, Hedgehogs [13] allow control over shape constraint tightness, see [13] for details. For partially ordered segments we generalize the starshape prior constraint as follows.  ... 
arXiv:1703.10530v1 fatcat:resycmrjobbxvcg6mupy3e4bja

Citation algorithms for identifying research milestones driving biomedical innovation

Jordan A. Comins, Loet Leydesdorff
2017 Scientometrics  
For instance, fundamental research on disease pathologies and mechanisms can generate potential targets for drug therapy.  ...  Scientific activity plays a major role in innovation for biomedicine and healthcare.  ...  Multi-RPYS extends the impact of these techniques by first segmenting the data in terms of the publication years of the citing sets, performing the standard RPYS analysis within each set and then rank  ... 
doi:10.1007/s11192-016-2238-1 fatcat:7sr4ffhkevhnpkjrleuulyjbla

Citation algorithms for identifying research milestones driving biomedical innovation [article]

Jordan A. Comins, Loet Leydesdorff
2016 arXiv   pre-print
For instance, fundamental research on disease pathologies and mechanisms can generate potential targets for drug therapy.  ...  Scientific activity plays a major role in innovation for biomedicine and healthcare.  ...  Multi-RPYS extends the impact of these techniques by first segmenting the data in terms of the publication years of the citing sets, performing the standard RPYS analysis within each set and then rank  ... 
arXiv:1611.01658v1 fatcat:khtwn7twmbaitfgbx3rjiutvmi

A Level Set Representation Method for $N$-Dimensional Convex Shape and Applications

Lingfeng Li
2021 Communications in Mathematical Research  
To the best of our knowledge, the proposed prior is the first one which can work for high dimensional objects. Convexity prior is very useful for object completion in computer vision.  ...  We apply this new method to two applications: object segmentation with convexity prior and convex hull problem (especially with outliers).  ...  Recently, generic and abstract shape priors have attracted more and more attention, such as connectivity [36] , star shape [34, 39] , hedgehog [18] and convexity [15, 33] .  ... 
doi:10.4208/cmr.2020-0034 fatcat:b5twviatxzhnxddchs3rblf7b4

A level set representation method for N-dimensional convex shape and applications [article]

Lingfeng li and Shousheng Luo and Xue-Cheng Tai and Jiang Yang
2020 arXiv   pre-print
We apply this new method to two applications: object segmentation with convexity prior and convex hull problem (especially with outliers).  ...  Convexity prior is very useful for object completion in computer vision. It is a very challenging task to design an efficient method for high dimensional convex objects representation.  ...  Recently, generic and abstract shape priors have attracted more and more attentions, such as connectivity [36] , star shape [34, 39] , hedgehog [19] and convexity [16, 33] .  ... 
arXiv:2003.09600v1 fatcat:x2uabbk2yjfzlow65bcg547ue4

IMG-19. RADIOMICS AND SUPERVISED DEEP LEARNING TO PREDICT MOLECULAR SUBGROUPS IN MEDULLOBLASTOMA BASED ON WHOLE TUMOR VOLUME LABELING: A SINGLE CENTER MULTIPARAMETRIC MR ANALYSIS

Ioan Paul Voicu, Piero Chiacchiaretta, Massimo Caulo, Evelina Miele, Alessia Carboni, Andrea Carai, Francesca Diomedi-Camassei, Sabrina Rossi, Antonella Cacchione, Giada Del Baldo, Elisabetta Ferretti, Angela Mastronuzzi (+2 others)
2020 Neuro-Oncology  
The most relevant features for classification were "simple" first-order features such as volume, major axis or shape.  ...  Solid tumor volumes were segmented semiautomatically. 107 features were extracted for each sequence (Pyradiomics, Python).  ...  Prior work by our group outlined a role for qualitative imaging features in aiding prognostication.  ... 
doi:10.1093/neuonc/noaa222.354 fatcat:vuy7ztvybvh4hoe6w4bktzvcfy

Interactive Phenotyping Of Large-Scale Histology Imaging Data With HistomicsML [article]

Michael Nalisnik, Mohamed Amgad, Sanghoon Lee, Sameer H. Halani, Jose Velazquez Vega, Daniel J. Brat, David A. Gutman, Lee A. D. Cooper
2017 bioRxiv   pre-print
These images can be mined to extract quantitative features that describe histologic elements, yielding measurements for hundreds of millions of objects.  ...  A central challenge in utilizing this data is enabling investigators to train and evaluate classification rules for identifying objects related to processes like angiogenesis or immune response.  ...  objects for rapid labeling.  ... 
doi:10.1101/140236 fatcat:we4jgrfpznazhkzdpfxereewge

iBOT: Image BERT Pre-Training with Online Tokenizer [article]

Jinghao Zhou, Chen Wei, Huiyu Wang, Wei Shen, Cihang Xie, Alan Yuille, Tao Kong
2022 arXiv   pre-print
The online tokenizer is jointly learnable with the MIM objective and dispenses with a multi-stage training pipeline where the tokenizer needs to be pre-trained beforehand.  ...  detection, instance segmentation, and semantic segmentation.  ...  We thank Li Dong and Hangbo Bao for sharing details of BEiT.  ... 
arXiv:2111.07832v3 fatcat:rojdktyjmveapdubvxcgdcfgn4

Grasping and Transport of Unstructured Collections of Massive Objects

Joseph Bowkett, Sisir Karumanchi, Renaud Detry
2022 Field Robotics  
The models address the problems of visual debris segmentation, object selection, and visual grasp planning.  ...  The object selector segments a debris pile into a set of parts that appear disjoint from one another and executes a rule-based decision program to select the object that appears easiest to extract.  ...  Contributors The authors would like to thank: tory for their support in generating media to depict the synthesis of grasps using the grasping pipeline described herein.  ... 
doi:10.55417/fr.2022014 fatcat:mqswpqskmzaltnciikgkpdtasq

Practice and challenges in trademark image retrieval

Jan Schietse, John P. Eakins, Remco C. Veltkamp
2007 Proceedings of the 6th ACM international conference on Image and video retrieval - CIVR '07  
Since the human expert can indicate the relative importance of certain elements/shapes, add tags to natural objects, and correct the segmentation results, we will start from an analyzed and enriched order  ...  of shapes and semantic features such as the presence of particular types of object.  ... 
doi:10.1145/1282280.1282355 dblp:conf/civr/SchietseEV07 fatcat:62ngiemq55gv7igb3xrgktve2e

Learning what is where from unlabeled images: joint localization and clustering of foreground objects

Ashok Chandrashekar, Lorenzo Torresani, Richard Granger
2013 Machine Learning  
However, unlike previous methods, objects are not assumed to be encapsulated by a single segment.  ...  We describe two methods for efficient foreground localization: the first method does not require any bottom-up image segmentation and discovers the foreground region as a contiguous rectangular bounding  ...  Acknowledgements The authors world like to thank Minh Hoai Nguyen for sharing his code for cosegmentation of image pairs.  ... 
doi:10.1007/s10994-013-5330-2 fatcat:kit34ajhqvdzffiopz7wxcsolq
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