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Items: 1 to 20 of 22

1.

A novel measure and significance testing in data analysis of cell image segmentation.

Wu JC, Halter M, Kacker RN, Elliott JT, Plant AL.

BMC Bioinformatics. 2017 Mar 14;18(1):168. doi: 10.1186/s12859-017-1527-x.

2.

Image Segmentation Using Hierarchical Merge Tree.

Liu T, Seyedhosseini M, Tasdizen T.

IEEE Trans Image Process. 2016 Jul 18. [Epub ahead of print]

PMID:
27448353
3.

Crowdsourcing the creation of image segmentation algorithms for connectomics.

Arganda-Carreras I, Turaga SC, Berger DR, Cireşan D, Giusti A, Gambardella LM, Schmidhuber J, Laptev D, Dwivedi S, Buhmann JM, Liu T, Seyedhosseini M, Tasdizen T, Kamentsky L, Burget R, Uher V, Tan X, Sun C, Pham TD, Bas E, Uzunbas MG, Cardona A, Schindelin J, Seung HS.

Front Neuroanat. 2015 Nov 5;9:142. doi: 10.3389/fnana.2015.00142. eCollection 2015.

4.

On the evaluation of segmentation editing tools.

Heckel F, Moltz JH, Meine H, Geisler B, Kießling A, D'Anastasi M, Dos Santos DP, Theruvath AJ, Hahn HK.

J Med Imaging (Bellingham). 2014 Oct;1(3):034005. doi: 10.1117/1.JMI.1.3.034005. Epub 2014 Nov 14.

5.

New breast cancer prognostic factors identified by computer-aided image analysis of HE stained histopathology images.

Chen JM, Qu AP, Wang LW, Yuan JP, Yang F, Xiang QM, Maskey N, Yang GF, Liu J, Li Y.

Sci Rep. 2015 May 29;5:10690. doi: 10.1038/srep10690.

6.

MRI segmentation of the human brain: challenges, methods, and applications.

Despotović I, Goossens B, Philips W.

Comput Math Methods Med. 2015;2015:450341. doi: 10.1155/2015/450341. Epub 2015 Mar 1. Review.

7.

SOAX: a software for quantification of 3D biopolymer networks.

Xu T, Vavylonis D, Tsai FC, Koenderink GH, Nie W, Yusuf E, I-Ju Lee, Wu JQ, Huang X.

Sci Rep. 2015 Mar 13;5:9081. doi: 10.1038/srep09081.

8.

Logistic Stick-Breaking Process.

Ren L, Du L, Carin L, Dunson DB.

J Mach Learn Res. 2011 Jan;12(Jan):203-239.

9.

A combined approach for the enhancement and segmentation of mammograms using modified fuzzy C-means method in wavelet domain.

Srivastava S, Sharma N, Singh SK, Srivastava R.

J Med Phys. 2014 Jul;39(3):169-83. doi: 10.4103/0971-6203.139007.

10.

Flexible methods for segmentation evaluation: results from CT-based luggage screening.

Karimi S, Jiang X, Cosman P, Martz H.

J Xray Sci Technol. 2014;22(2):175-95. doi: 10.3233/XST-140418.

11.

Quantitative protein localization signatures reveal an association between spatial and functional divergences of proteins.

Loo LH, Laksameethanasan D, Tung YL.

PLoS Comput Biol. 2014 Mar 6;10(3):e1003504. doi: 10.1371/journal.pcbi.1003504. eCollection 2014 Mar.

12.

cellXpress: a fast and user-friendly software platform for profiling cellular phenotypes.

Laksameethanasan D, Tan R, Toh G, Loo LH.

BMC Bioinformatics. 2013;14 Suppl 16:S4. doi: 10.1186/1471-2105-14-S16-S4. Epub 2013 Oct 22.

13.

Eliminating tissue-fold artifacts in histopathological whole-slide images for improved image-based prediction of cancer grade.

Kothari S, Phan JH, Wang MD.

J Pathol Inform. 2013 Aug 31;4:22. doi: 10.4103/2153-3539.117448. eCollection 2013.

14.

Automatic screening for tuberculosis in chest radiographs: a survey.

Jaeger S, Karargyris A, Candemir S, Siegelman J, Folio L, Antani S, Thoma G.

Quant Imaging Med Surg. 2013 Apr;3(2):89-99. doi: 10.3978/j.issn.2223-4292.2013.04.03.

15.

A rate-distortion-based merging algorithm for compressed image segmentation.

Juang YS, Hsin HC, Sung TY, Shieh YS, Cattani C.

Comput Math Methods Med. 2012;2012:648320. doi: 10.1155/2012/648320. Epub 2012 Oct 15.

16.

Minimizing manual image segmentation turn-around time for neuronal reconstruction by embracing uncertainty.

Plaza SM, Scheffer LK, Saunders M.

PLoS One. 2012;7(9):e44448. doi: 10.1371/journal.pone.0044448. Epub 2012 Sep 21.

17.

Gaussian multiscale aggregation applied to segmentation in hand biometrics.

de Santos Sierra A, Avila CS, Casanova JG, del Pozo GB.

Sensors (Basel). 2011;11(12):11141-56. doi: 10.3390/s111211141. Epub 2011 Nov 28.

18.

Gebiss: an ImageJ plugin for the specification of ground truth and the performance evaluation of 3D segmentation algorithms.

Kriston-Vizi J, Thong NW, Poh CL, Yee KC, Ling JS, Kraut R, Wasser M.

BMC Bioinformatics. 2011 Jun 13;12:232. doi: 10.1186/1471-2105-12-232.

19.

Evaluating segmentation algorithms for diffusion-weighted MR images: a task-based approach.

Jha AK, Kupinski MA, Rodríguez JJ, Stephen RM, Stopeck AT.

Proc SPIE Int Soc Opt Eng. 2010 Feb 27;7627. pii: 76270L (2010).

20.

Machines that learn to segment images: a crucial technology for connectomics.

Jain V, Seung HS, Turaga SC.

Curr Opin Neurobiol. 2010 Oct;20(5):653-66. doi: 10.1016/j.conb.2010.07.004. Review.

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