503 related articles for article (PubMed ID: 28966837)
1. A Methodology for Texture Feature-based Quality Assessment in Nucleus Segmentation of Histopathology Image.
Wen S; Kurc TM; Gao Y; Zhao T; Saltz JH; Zhu W
J Pathol Inform; 2017; 8():38. PubMed ID: 28966837
[TBL] [Abstract][Full Text] [Related]
2. Ranked retrieval of segmented nuclei for objective assessment of cancer gene repositioning.
Cukierski WJ; Nandy K; Gudla P; Meaburn KJ; Misteli T; Foran DJ; Lockett SJ
BMC Bioinformatics; 2012 Sep; 13():232. PubMed ID: 22971117
[TBL] [Abstract][Full Text] [Related]
3. Comparison of Different Classifiers with Active Learning to Support Quality Control in Nucleus Segmentation in Pathology Images.
Wen S; Kurc TM; Hou L; Saltz JH; Gupta RR; Batiste R; Zhao T; Nguyen V; Samaras D; Zhu W
AMIA Jt Summits Transl Sci Proc; 2018; 2017():227-236. PubMed ID: 29888078
[TBL] [Abstract][Full Text] [Related]
4. Robust detection and segmentation of cell nuclei in biomedical images based on a computational topology framework.
Rojas-Moraleda R; Xiong W; Halama N; Breitkopf-Heinlein K; Dooley S; Salinas L; Heermann DW; Valous NA
Med Image Anal; 2017 May; 38():90-103. PubMed ID: 28314191
[TBL] [Abstract][Full Text] [Related]
5. A data model and database for high-resolution pathology analytical image informatics.
Wang F; Kong J; Cooper L; Pan T; Kurc T; Chen W; Sharma A; Niedermayr C; Oh TW; Brat D; Farris AB; Foran DJ; Saltz J
J Pathol Inform; 2011; 2():32. PubMed ID: 21845230
[TBL] [Abstract][Full Text] [Related]
6. Multi-atlas segmentation of the whole hippocampus and subfields using multiple automatically generated templates.
Pipitone J; Park MT; Winterburn J; Lett TA; Lerch JP; Pruessner JC; Lepage M; Voineskos AN; Chakravarty MM;
Neuroimage; 2014 Nov; 101():494-512. PubMed ID: 24784800
[TBL] [Abstract][Full Text] [Related]
7. Automated discrimination of lower and higher grade gliomas based on histopathological image analysis.
Mousavi HS; Monga V; Rao G; Rao AU
J Pathol Inform; 2015; 6():15. PubMed ID: 25838967
[TBL] [Abstract][Full Text] [Related]
8. Fast and accurate tumor segmentation of histology images using persistent homology and deep convolutional features.
Qaiser T; Tsang YW; Taniyama D; Sakamoto N; Nakane K; Epstein D; Rajpoot N
Med Image Anal; 2019 Jul; 55():1-14. PubMed ID: 30991188
[TBL] [Abstract][Full Text] [Related]
9. Multi-layer pseudo-supervision for histopathology tissue semantic segmentation using patch-level classification labels.
Han C; Lin J; Mai J; Wang Y; Zhang Q; Zhao B; Chen X; Pan X; Shi Z; Xu Z; Yao S; Yan L; Lin H; Huang X; Liang C; Han G; Liu Z
Med Image Anal; 2022 Aug; 80():102487. PubMed ID: 35671591
[TBL] [Abstract][Full Text] [Related]
10. Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification.
Marini N; Otálora S; Müller H; Atzori M
Med Image Anal; 2021 Oct; 73():102165. PubMed ID: 34303169
[TBL] [Abstract][Full Text] [Related]
11. Segmentation of white blood cells and comparison of cell morphology by linear and naïve Bayes classifiers.
Prinyakupt J; Pluempitiwiriyawej C
Biomed Eng Online; 2015 Jun; 14():63. PubMed ID: 26123131
[TBL] [Abstract][Full Text] [Related]
12. Hierarchical multi-atlas label fusion with multi-scale feature representation and label-specific patch partition.
Wu G; Kim M; Sanroma G; Wang Q; Munsell BC; Shen D;
Neuroimage; 2015 Feb; 106():34-46. PubMed ID: 25463474
[TBL] [Abstract][Full Text] [Related]
13. AutoIHC-Analyzer: computer-assisted microscopy for automated membrane extraction/scoring in HER2 molecular markers.
Tewary S; Arun I; Ahmed R; Chatterjee S; Mukhopadhyay S
J Microsc; 2021 Jan; 281(1):87-96. PubMed ID: 32803890
[TBL] [Abstract][Full Text] [Related]
14. Efficient COVID-19 CT Scan Image Segmentation by Automatic Clustering Algorithm.
Shivahare BD; Gupta SK
J Healthc Eng; 2022; 2022():9009406. PubMed ID: 35368938
[TBL] [Abstract][Full Text] [Related]
15. Methods for Segmentation and Classification of Digital Microscopy Tissue Images.
Vu QD; Graham S; Kurc T; To MNN; Shaban M; Qaiser T; Koohbanani NA; Khurram SA; Kalpathy-Cramer J; Zhao T; Gupta R; Kwak JT; Rajpoot N; Saltz J; Farahani K
Front Bioeng Biotechnol; 2019; 7():53. PubMed ID: 31001524
[TBL] [Abstract][Full Text] [Related]
16. Method: automatic segmentation of mitochondria utilizing patch classification, contour pair classification, and automatically seeded level sets.
Giuly RJ; Martone ME; Ellisman MH
BMC Bioinformatics; 2012 Feb; 13():29. PubMed ID: 22321695
[TBL] [Abstract][Full Text] [Related]
17. A dual autoencoder and singular value decomposition based feature optimization for the segmentation of brain tumor from MRI images.
Aswani K; Menaka D
BMC Med Imaging; 2021 May; 21(1):82. PubMed ID: 33985449
[TBL] [Abstract][Full Text] [Related]
18. A semiautomatic segmentation method for prostate in CT images using local texture classification and statistical shape modeling.
Shahedi M; Halicek M; Guo R; Zhang G; Schuster DM; Fei B
Med Phys; 2018 Jun; 45(6):2527-2541. PubMed ID: 29611216
[TBL] [Abstract][Full Text] [Related]
19. Dataset of segmented nuclei in hematoxylin and eosin stained histopathology images of ten cancer types.
Hou L; Gupta R; Van Arnam JS; Zhang Y; Sivalenka K; Samaras D; Kurc TM; Saltz JH
Sci Data; 2020 Jun; 7(1):185. PubMed ID: 32561748
[TBL] [Abstract][Full Text] [Related]
20. Influence of segmentation margin on machine learning-based high-dimensional quantitative CT texture analysis: a reproducibility study on renal clear cell carcinomas.
Kocak B; Ates E; Durmaz ES; Ulusan MB; Kilickesmez O
Eur Radiol; 2019 Sep; 29(9):4765-4775. PubMed ID: 30747300
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
