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Hedgehog Shape Priors for Multi-Object Segmentation
2016
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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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]
2016
arXiv
pre-print
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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]
2018
Lecture Notes in Computer Science
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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)
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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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]
2017
arXiv
pre-print
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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
2017
Scientometrics
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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]
2016
arXiv
pre-print
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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
2021
Communications in Mathematical Research
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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]
2020
arXiv
pre-print
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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
2020
Neuro-Oncology
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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]
2017
bioRxiv
pre-print
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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]
2022
arXiv
pre-print
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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
2022
Field Robotics
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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
2007
Proceedings of the 6th ACM international conference on Image and video retrieval - CIVR '07
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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
2013
Machine Learning
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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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