These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

130 related articles for article (PubMed ID: 27406956)

  • 1. Computer aided detection and classification of acute lymphoblastic leukemia cell subtypes based on microscopic image analysis.
    MoradiAmin M; Memari A; Samadzadehaghdam N; Kermani S; Talebi A
    Microsc Res Tech; 2016 Oct; 79(10):908-916. PubMed ID: 27406956
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Recognition of acute lymphoblastic leukemia and lymphocytes cell subtypes in microscopic images using random forest classifier.
    Mirmohammadi P; Ameri M; Shalbaf A
    Phys Eng Sci Med; 2021 Jun; 44(2):433-441. PubMed ID: 33751420
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Recognition of acute lymphoblastic leukemia cells in microscopic images using k-means clustering and support vector machine classifier.
    Amin MM; Kermani S; Talebi A; Oghli MG
    J Med Signals Sens; 2015; 5(1):49-58. PubMed ID: 25709941
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Acute Lymphoblastic Leukemia Detection and Classification of Its Subtypes Using Pretrained Deep Convolutional Neural Networks.
    Shafique S; Tehsin S
    Technol Cancer Res Treat; 2018 Jan; 17():1533033818802789. PubMed ID: 30261827
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Automatic classification of acute lymphoblastic leukemia cells and lymphocyte subtypes based on a novel convolutional neural network.
    MoradiAmin M; Yousefpour M; Samadzadehaghdam N; Ghahari L; Ghorbani M; Mafi M
    Microsc Res Tech; 2024 Jul; 87(7):1615-1626. PubMed ID: 38445461
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Detection of acute lymphoblastic leukemia using image segmentation and data mining algorithms.
    Acharya V; Kumar P
    Med Biol Eng Comput; 2019 Aug; 57(8):1783-1811. PubMed ID: 31201595
    [TBL] [Abstract][Full Text] [Related]  

  • 7. An Automatic and Robust Decision Support System for Accurate Acute Leukemia Diagnosis from Blood Microscopic Images.
    Moshavash Z; Danyali H; Helfroush MS
    J Digit Imaging; 2018 Oct; 31(5):702-717. PubMed ID: 29654425
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Classification of acute lymphoblastic leukemia using deep learning.
    Rehman A; Abbas N; Saba T; Rahman SIU; Mehmood Z; Kolivand H
    Microsc Res Tech; 2018 Nov; 81(11):1310-1317. PubMed ID: 30351463
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Multi-Method Diagnosis of Blood Microscopic Sample for Early Detection of Acute Lymphoblastic Leukemia Based on Deep Learning and Hybrid Techniques.
    Abunadi I; Senan EM
    Sensors (Basel); 2022 Feb; 22(4):. PubMed ID: 35214531
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Computer-Aided Diagnosis of Acute Lymphoblastic Leukaemia.
    Shafique S; Tehsin S
    Comput Math Methods Med; 2018; 2018():6125289. PubMed ID: 29681996
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Automatic Recognition of Acute Myelogenous Leukemia in Blood Microscopic Images Using K-means Clustering and Support Vector Machine.
    Kazemi F; Najafabadi TA; Araabi BN
    J Med Signals Sens; 2016; 6(3):183-93. PubMed ID: 27563575
    [TBL] [Abstract][Full Text] [Related]  

  • 12. An Intelligent Decision Support System for Leukaemia Diagnosis using Microscopic Blood Images.
    Chin Neoh S; Srisukkham W; Zhang L; Todryk S; Greystoke B; Peng Lim C; Alamgir Hossain M; Aslam N
    Sci Rep; 2015 Oct; 5():14938. PubMed ID: 26450665
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Mutual Information based hybrid model and deep learning for Acute Lymphocytic Leukemia detection in single cell blood smear images.
    Jha KK; Dutta HS
    Comput Methods Programs Biomed; 2019 Oct; 179():104987. PubMed ID: 31443862
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Automatic detection and classification of leukocytes using convolutional neural networks.
    Zhao J; Zhang M; Zhou Z; Chu J; Cao F
    Med Biol Eng Comput; 2017 Aug; 55(8):1287-1301. PubMed ID: 27822698
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Nucleus and cytoplasm-based segmentation and actor-critic neural network for acute lymphocytic leukaemia detection in single cell blood smear images.
    Jha KK; Dutta HS
    Med Biol Eng Comput; 2020 Jan; 58(1):171-186. PubMed ID: 31811554
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Feature Analysis and Automatic Identification of Leukemic Lineage Blast Cells and Reactive Lymphoid Cells from Peripheral Blood Cell Images.
    Bigorra L; Merino A; Alférez S; Rodellar J
    J Clin Lab Anal; 2017 Mar; 31(2):. PubMed ID: 27427422
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A robust classification of acute lymphocytic leukemia-based microscopic images with supervised Hilbert-Huang transform.
    Elrefaie RM; Mohamed MA; Marzouk EA; Ata MM
    Microsc Res Tech; 2024 Feb; 87(2):191-204. PubMed ID: 37715495
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Segmentation and Classification of Bone Marrow Cells Images Using Contextual Information for Medical Diagnosis of Acute Leukemias.
    Reta C; Altamirano L; Gonzalez JA; Diaz-Hernandez R; Peregrina H; Olmos I; Alonso JE; Lobato R
    PLoS One; 2015; 10(6):e0130805. PubMed ID: 26107374
    [TBL] [Abstract][Full Text] [Related]  

  • 19. The monitoring of acute leukemia patients: Part 1. Basic morphometric characteristics of bone marrow blast cells in acute lymphoblastic leukemia.
    Pogorelov VM; Timkina EN; Mattes G; Ile R; Miterev GYu ; Novikova MS; Isaev VG; Kozinetz GI
    Leuk Res; 1990; 14(9):795-800. PubMed ID: 2232851
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Acute leukemia classification by ensemble particle swarm model selection.
    Escalante HJ; Montes-y-Gómez M; González JA; Gómez-Gil P; Altamirano L; Reyes CA; Reta C; Rosales A
    Artif Intell Med; 2012 Jul; 55(3):163-75. PubMed ID: 22510477
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.