44 related articles for article (PubMed ID: 28815426)
1. Identification and red blood cell automated counting from blood smear images using computer-aided system.
Acharya V; Kumar P
Med Biol Eng Comput; 2018 Mar; 56(3):483-489. PubMed ID: 28815426
[TBL] [Abstract][Full Text] [Related]
2. Bio-net dataset: AI-based diagnostic solutions using peripheral blood smear images.
Shams UA; Javed I; Fizan M; Shah AR; Mustafa G; Zubair M; Massoud Y; Mehmood MQ; Naveed MA
Blood Cells Mol Dis; 2024 Mar; 105():102823. PubMed ID: 38241949
[TBL] [Abstract][Full Text] [Related]
3. Automatic classification of cells in microscopic fecal images using convolutional neural networks.
Du X; Liu L; Wang X; Ni G; Zhang J; Hao R; Liu J; Liu Y
Biosci Rep; 2019 Apr; 39(4):. PubMed ID: 30872411
[TBL] [Abstract][Full Text] [Related]
4. Automated image analysis to assess hygienic behaviour of honeybees.
Paolillo G; Petrini A; Casiraghi E; De Iorio MG; Biffani S; Pagnacco G; Minozzi G; Valentini G
PLoS One; 2022; 17(1):e0263183. PubMed ID: 35085372
[TBL] [Abstract][Full Text] [Related]
5. Leukemia segmentation and classification: A comprehensive survey.
Saleem S; Amin J; Sharif M; Mallah GA; Kadry S; Gandomi AH
Comput Biol Med; 2022 Nov; 150():106028. PubMed ID: 36126356
[TBL] [Abstract][Full Text] [Related]
6. A Novel Four-Step Algorithm for Detecting a Single Circle in Complex Images.
Cao J; Gao Y; Wang C
Sensors (Basel); 2023 Nov; 23(22):. PubMed ID: 38005418
[TBL] [Abstract][Full Text] [Related]
7. Foci-Xpress: Automated and Fast Nuclear Foci Counting Tool.
Moon JI; Kim WJ; Kim KT; Kim HJ; Shin HR; Yoon H; Park SG; Park MS; Cho YD; Kim PJ; Ryoo HM
Int J Mol Sci; 2023 Sep; 24(19):. PubMed ID: 37833912
[TBL] [Abstract][Full Text] [Related]
8. Optical counting platform of shrimp larvae using masked k-means and a side window filter.
Qian K; Duan HC
Appl Opt; 2024 Feb; 63(6):A7-A15. PubMed ID: 38437352
[TBL] [Abstract][Full Text] [Related]
9. Automated Spot Counting in Microbiology.
Lin CP; Duan Y; Sargsyan D; Cabrera J; Livingston CM; Vogel R; Hartman J; Das M; Talloen W; Geys H; Kanoulas ED; Mohanty S
IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(6):3703-3714. PubMed ID: 37725729
[TBL] [Abstract][Full Text] [Related]
10. Assessing the suitability of cell counting methods during different stages of a cell processing workflow using an ISO 20391-2 guided study design and analysis.
Richards C; Sarkar S; Kandell J; Snyder R; Lakshmipathy U
Front Bioeng Biotechnol; 2023; 11():1223227. PubMed ID: 37600315
[TBL] [Abstract][Full Text] [Related]
11. A high-resolution large-scale dataset of pathological and normal white blood cells.
Bodzas A; Kodytek P; Zidek J
Sci Data; 2023 Jul; 10(1):466. PubMed ID: 37468490
[TBL] [Abstract][Full Text] [Related]
12. Evaluation of complete blood count results from a new, on-site hemocytometer compared with a laboratory-based hemocytometer.
Despotis GJ; Alsoufiev A; Hogue CW; Zoys TN; Goodnough LT; Santoro SA; Kater KM; Barnes P; Lappas DG
Crit Care Med; 1996 Jul; 24(7):1163-7. PubMed ID: 8674329
[TBL] [Abstract][Full Text] [Related]
13. Crowdsourced human-based computational approach for tagging peripheral blood smear sample images from Sickle Cell Disease patients using non-expert users.
Rubio JMB; Moyà-Alcover G; Jaume-I-Capó A; Petrović N
Sci Rep; 2024 Jan; 14(1):1201. PubMed ID: 38216623
[TBL] [Abstract][Full Text] [Related]
14. Quantification and Characterization of CTCs and Clusters in Pancreatic Cancer by Means of the Hough Transform Algorithm.
Calero-Castro FJ; Pereira S; Laga I; Villanueva P; Suárez-Artacho G; Cepeda-Franco C; de la Cruz-Ojeda P; Navarro-Villarán E; Dios-Barbeito S; Serrano MJ; Fresno C; Padillo-Ruiz J
Int J Mol Sci; 2023 Feb; 24(5):. PubMed ID: 36901704
[TBL] [Abstract][Full Text] [Related]
15. White blood cell classification via a discriminative region detection assisted feature aggregation network.
Jiang L; Tang C; Zhou H
Biomed Opt Express; 2022 Oct; 13(10):5246-5260. PubMed ID: 36425625
[TBL] [Abstract][Full Text] [Related]
16. Analysis of red blood cells from peripheral blood smear images for anemia detection: a methodological review.
K T N; Prasad K; Singh BMK
Med Biol Eng Comput; 2022 Sep; 60(9):2445-2462. PubMed ID: 35838854
[TBL] [Abstract][Full Text] [Related]
17. High-throughput label-free cell detection and counting from diffraction patterns with deep fully convolutional neural networks.
Yi F; Park S; Moon I
J Biomed Opt; 2021 Mar; 26(3):. PubMed ID: 33686845
[TBL] [Abstract][Full Text] [Related]
18. Machine learning approach of automatic identification and counting of blood cells.
Alam MM; Islam MT
Healthc Technol Lett; 2019 Aug; 6(4):103-108. PubMed ID: 31531224
[TBL] [Abstract][Full Text] [Related]
19. Non-Invasive Method to Estimate Red Blood Cell in Blood.
Quiñonez Y; Almeraya S; Almeraya S; Reyna J; Mejía J
J Med Syst; 2019 Sep; 43(10):316. PubMed ID: 31506773
[TBL] [Abstract][Full Text] [Related]
20. Micro-Droplet Detection Method for Measuring the Concentration of Alkaline Phosphatase-Labeled Nanoparticles in Fluorescence Microscopy.
Li R; Wang Y; Xu H; Fei B; Qin B
Sensors (Basel); 2017 Nov; 17(11):. PubMed ID: 29160812
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
