167 related articles for article (PubMed ID: 23888106)
1. Statistical Shape Model for Manifold Regularization: Gleason grading of prostate histology.
Sparks R; Madabhushi A
Comput Vis Image Underst; 2013 Sep; 117(9):1138-1146. PubMed ID: 23888106
[TBL] [Abstract][Full Text] [Related]
2. Explicit shape descriptors: novel morphologic features for histopathology classification.
Sparks R; Madabhushi A
Med Image Anal; 2013 Dec; 17(8):997-1009. PubMed ID: 23850744
[TBL] [Abstract][Full Text] [Related]
3. Automated gleason grading on prostate biopsy slides by statistical representations of homology profile.
Yan C; Nakane K; Wang X; Fu Y; Lu H; Fan X; Feldman MD; Madabhushi A; Xu J
Comput Methods Programs Biomed; 2020 Oct; 194():105528. PubMed ID: 32470903
[TBL] [Abstract][Full Text] [Related]
4. Out-of-Sample Extrapolation utilizing Semi-Supervised Manifold Learning (OSE-SSL): Content Based Image Retrieval for Histopathology Images.
Sparks R; Madabhushi A
Sci Rep; 2016 Jun; 6():27306. PubMed ID: 27264985
[TBL] [Abstract][Full Text] [Related]
5. Persistent Homology for the Quantitative Evaluation of Architectural Features in Prostate Cancer Histology.
Lawson P; Sholl AB; Brown JQ; Fasy BT; Wenk C
Sci Rep; 2019 Feb; 9(1):1139. PubMed ID: 30718811
[TBL] [Abstract][Full Text] [Related]
6. Going deeper through the Gleason scoring scale: An automatic end-to-end system for histology prostate grading and cribriform pattern detection.
Silva-Rodríguez J; Colomer A; Sales MA; Molina R; Naranjo V
Comput Methods Programs Biomed; 2020 Oct; 195():105637. PubMed ID: 32653747
[TBL] [Abstract][Full Text] [Related]
7. Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study.
Bulten W; Pinckaers H; van Boven H; Vink R; de Bel T; van Ginneken B; van der Laak J; Hulsbergen-van de Kaa C; Litjens G
Lancet Oncol; 2020 Feb; 21(2):233-241. PubMed ID: 31926805
[TBL] [Abstract][Full Text] [Related]
8. Novel morphometric based classification via diffeomorphic based shape representation using manifold learning.
Sparks R; Madabhushi A
Med Image Comput Comput Assist Interv; 2010; 13(Pt 3):658-65. PubMed ID: 20879457
[TBL] [Abstract][Full Text] [Related]
9. Exploring automatic prostate histopathology image Gleason grading via local structure modeling.
Wang D; Foran DJ; Ren J; Zhong H; Kim IY; Qi X
Annu Int Conf IEEE Eng Med Biol Soc; 2015; 2015():2649-52. PubMed ID: 26736836
[TBL] [Abstract][Full Text] [Related]
10. Automatic diagnosis and grading of Prostate Cancer with weakly supervised learning on whole slide images.
Xiang J; Wang X; Wang X; Zhang J; Yang S; Yang W; Han X; Liu Y
Comput Biol Med; 2023 Jan; 152():106340. PubMed ID: 36481762
[TBL] [Abstract][Full Text] [Related]
11. Deep Learning-Based Gleason Grading of Prostate Cancer From Histopathology Images-Role of Multiscale Decision Aggregation and Data Augmentation.
Karimi D; Nir G; Fazli L; Black PC; Goldenberg L; Salcudean SE
IEEE J Biomed Health Inform; 2020 May; 24(5):1413-1426. PubMed ID: 31567104
[TBL] [Abstract][Full Text] [Related]
12. Computer aided analysis of prostate histopathology images to support a refined Gleason grading system.
Ren J; Sadimin E; Foran DJ; Qi X
Proc SPIE Int Soc Opt Eng; 2017 Jan; 10133():. PubMed ID: 30828124
[TBL] [Abstract][Full Text] [Related]
13. Transfer Learning with Pretrained Convolutional Neural Network for Automated Gleason Grading of Prostate Cancer Tissue Microarrays.
Gifani P; Shalbaf A
J Med Signals Sens; 2024; 14():4. PubMed ID: 38510670
[TBL] [Abstract][Full Text] [Related]
14. Association between Nuclear Morphometry Parameters and Gleason Grade in Patients with Prostatic Cancer.
Malshy K; Amiel GE; Hershkovitz D; Sabo E; Hoffman A
Diagnostics (Basel); 2022 May; 12(6):. PubMed ID: 35741165
[TBL] [Abstract][Full Text] [Related]
15. The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma: Definition of Grading Patterns and Proposal for a New Grading System.
Epstein JI; Egevad L; Amin MB; Delahunt B; Srigley JR; Humphrey PA;
Am J Surg Pathol; 2016 Feb; 40(2):244-52. PubMed ID: 26492179
[TBL] [Abstract][Full Text] [Related]
16. More advantages in detecting bone and soft tissue metastases from prostate cancer using
Pianou NK; Stavrou PZ; Vlontzou E; Rondogianni P; Exarhos DN; Datseris IE
Hell J Nucl Med; 2019; 22(1):6-9. PubMed ID: 30843003
[TBL] [Abstract][Full Text] [Related]
17. Automatic grading of prostate cancer in digitized histopathology images: Learning from multiple experts.
Nir G; Hor S; Karimi D; Fazli L; Skinnider BF; Tavassoli P; Turbin D; Villamil CF; Wang G; Wilson RS; Iczkowski KA; Lucia MS; Black PC; Abolmaesumi P; Goldenberg SL; Salcudean SE
Med Image Anal; 2018 Dec; 50():167-180. PubMed ID: 30340027
[TBL] [Abstract][Full Text] [Related]
18. Multi-kernel graph embedding for detection, Gleason grading of prostate cancer via MRI/MRS.
Tiwari P; Kurhanewicz J; Madabhushi A
Med Image Anal; 2013 Feb; 17(2):219-35. PubMed ID: 23294985
[TBL] [Abstract][Full Text] [Related]
19. Identifying the morphologic basis for radiomic features in distinguishing different Gleason grades of prostate cancer on MRI: Preliminary findings.
Penzias G; Singanamalli A; Elliott R; Gollamudi J; Shih N; Feldman M; Stricker PD; Delprado W; Tiwari S; Böhm M; Haynes AM; Ponsky L; Fu P; Tiwari P; Viswanath S; Madabhushi A
PLoS One; 2018; 13(8):e0200730. PubMed ID: 30169514
[TBL] [Abstract][Full Text] [Related]
20. Nondestructive 3D pathology with analysis of nuclear features for prostate cancer risk assessment.
Serafin R; Koyuncu C; Xie W; Huang H; Glaser AK; Reder NP; Janowczyk A; True LD; Madabhushi A; Liu JT
J Pathol; 2023 Aug; 260(4):390-401. PubMed ID: 37232213
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
