159 related articles for article (PubMed ID: 36853796)
21. A shape context fully convolutional neural network for segmentation and classification of cervical nuclei in Pap smear images.
Hussain E; Mahanta LB; Das CR; Choudhury M; Chowdhury M
Artif Intell Med; 2020 Jul; 107():101897. PubMed ID: 32828445
[TBL] [Abstract][Full Text] [Related]
22. Automatic Bone Marrow Cellularity Estimation in H&E Stained Whole Slide Images.
Nielsen FS; Pedersen MJ; Olsen MV; Larsen MS; Røge R; Jørgensen AS
Cytometry A; 2019 Oct; 95(10):1066-1074. PubMed ID: 31490627
[TBL] [Abstract][Full Text] [Related]
23. Automated segmentation of cell membranes to evaluate HER2 status in whole slide images using a modified deep learning network.
Khameneh FD; Razavi S; Kamasak M
Comput Biol Med; 2019 Jul; 110():164-174. PubMed ID: 31163391
[TBL] [Abstract][Full Text] [Related]
24. Combined evaluation of bone marrow aspirate and biopsy is superior in the prognosis of multiple myeloma.
Stifter S; Babarović E; Valković T; Seili-Bekafigo I; Stemberger C; Nacinović A; Lucin K; Jonjić N
Diagn Pathol; 2010 May; 5():30. PubMed ID: 20482792
[TBL] [Abstract][Full Text] [Related]
25. A pyramidal deep learning pipeline for kidney whole-slide histology images classification.
Abdeltawab H; Khalifa F; Ghazal M; Cheng L; Gondim D; El-Baz A
Sci Rep; 2021 Oct; 11(1):20189. PubMed ID: 34642404
[TBL] [Abstract][Full Text] [Related]
26. 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]
27. A benchmark bone marrow aspirate smear dataset and a multi-scale cell detection model for the diagnosis of hematological disorders.
Su J; Han J; Song J
Comput Med Imaging Graph; 2021 Jun; 90():101912. PubMed ID: 33892388
[TBL] [Abstract][Full Text] [Related]
28. Semantic focusing allows fully automated single-layer slide scanning of cervical cytology slides.
Lahrmann B; Valous NA; Eisenmann U; Wentzensen N; Grabe N
PLoS One; 2013; 8(4):e61441. PubMed ID: 23585899
[TBL] [Abstract][Full Text] [Related]
29. Developing a Machine Learning Algorithm for Identifying Abnormal Urothelial Cells: A Feasibility Study.
Zhang Z; Fu X; Liu J; Huang Z; Liu N; Fang F; Rao J
Acta Cytol; 2021; 65(4):335-341. PubMed ID: 33022673
[TBL] [Abstract][Full Text] [Related]
30. Nucleated Cell Count Has Negligible Predictive Value for the Number of Colony-Forming Units for Connective Tissue Progenitor Cells (Stem Cells) in Bone Marrow Aspirate Harvested From the Proximal Humerus During Arthroscopic Rotator Cuff Repair.
Muench LN; Berthold DP; Kia C; Otto A; Cote MP; McCarthy MB; Mazzocca AD; Mehl J
Arthroscopy; 2021 Jul; 37(7):2043-2052. PubMed ID: 33581306
[TBL] [Abstract][Full Text] [Related]
31. Counting and differential of bone marrow cells by an electronic method.
Tatsumi J; Tatsumi Y; Tatsumi N
Am J Clin Pathol; 1986 Jul; 86(1):50-4. PubMed ID: 3728383
[TBL] [Abstract][Full Text] [Related]
32. An artificial intelligent diagnostic system on differential recognition of hematopoietic cells from microscopic images.
Beksaç M; Beksaç MS; Tipi VB; Duru HA; Karakás MU; Cakar AN
Cytometry; 1997 Jun; 30(3):145-50. PubMed ID: 9222100
[TBL] [Abstract][Full Text] [Related]
33. Optimal aspiration volume of vertebral bone marrow for use in spinal fusion.
Hustedt JW; Jegede KA; Badrinath R; Bohl DD; Blizzard DJ; Grauer JN
Spine J; 2013 Oct; 13(10):1217-22. PubMed ID: 24075028
[TBL] [Abstract][Full Text] [Related]
34. Automated enumeration of cellular composition in bone marrow aspirate with the CELL-DYN 4000 automated hematology analyzer.
Sakamoto C; Yamane T; Ohta K; Hino M; Tsuda I; Tatsumi N
Acta Haematol; 1999; 101(3):130-4. PubMed ID: 10352331
[TBL] [Abstract][Full Text] [Related]
35. Digital Microscopy Augmented by Artificial Intelligence to Interpret Bone Marrow Samples for Hematological Diseases.
Bermejo-Peláez D; Rueda Charro S; García Roa M; Trelles-Martínez R; Bobes-Fernández A; Hidalgo Soto M; García-Vicente R; Morales ML; Rodríguez-García A; Ortiz-Ruiz A; Blanco Sánchez A; Mousa Urbina A; Álamo E; Lin L; Dacal E; Cuadrado D; Postigo M; Vladimirov A; Garcia-Villena J; Santos A; Ledesma-Carbayo MJ; Ayala R; Martínez-López J; Linares M; Luengo-Oroz M
Microsc Microanal; 2024 Mar; 30(1):151-159. PubMed ID: 38302194
[TBL] [Abstract][Full Text] [Related]
36. Automated diagnosis of 7 canine skin tumors using machine learning on H&E-stained whole slide images.
Fragoso-Garcia M; Wilm F; Bertram CA; Merz S; Schmidt A; Donovan T; Fuchs-Baumgartinger A; Bartel A; Marzahl C; Diehl L; Puget C; Maier A; Aubreville M; Breininger K; Klopfleisch R
Vet Pathol; 2023 Nov; 60(6):865-875. PubMed ID: 37515411
[TBL] [Abstract][Full Text] [Related]
37. DeepFocus: Detection of out-of-focus regions in whole slide digital images using deep learning.
Senaras C; Niazi MKK; Lozanski G; Gurcan MN
PLoS One; 2018; 13(10):e0205387. PubMed ID: 30359393
[TBL] [Abstract][Full Text] [Related]
38. Metastasis detection from whole slide images using local features and random forests.
Valkonen M; Kartasalo K; Liimatainen K; Nykter M; Latonen L; Ruusuvuori P
Cytometry A; 2017 Jun; 91(6):555-565. PubMed ID: 28426134
[TBL] [Abstract][Full Text] [Related]
39. Developing and Preliminary Validating an Automatic Cell Classification System for Bone Marrow Smears: a Pilot Study.
Jin H; Fu X; Cao X; Sun M; Wang X; Zhong Y; Yang S; Qi C; Peng B; He X; He F; Jiang Y; Gao H; Li S; Huang Z; Li Q; Fang F; Zhang J
J Med Syst; 2020 Sep; 44(10):184. PubMed ID: 32894360
[TBL] [Abstract][Full Text] [Related]
40. State of the Art Cell Detection in Bone Marrow Whole Slide Images.
Gräbel P; Özkan Ö; Crysandt M; Herwartz R; Baumann M; Klinkhammer BM; Boor P; Brümmendorf TH; Merhof D
J Pathol Inform; 2021; 12():36. PubMed ID: 34760333
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]