144 related articles for article (PubMed ID: 31846832)
1. Interferometer eye image classification for dry eye categorization using phylogenetic diversity indexes for texture analysis.
da Cruz LB; Souza JC; de Sousa JA; Santos AM; de Paiva AC; de Almeida JDS; Silva AC; Junior GB; Gattass M
Comput Methods Programs Biomed; 2020 May; 188():105269. PubMed ID: 31846832
[TBL] [Abstract][Full Text] [Related]
2. Tear Film Classification in Interferometry Eye Images Using Phylogenetic Diversity Indexes and Ripley's K Function.
da Cruz LB; Souza JC; de Paiva AC; de Almeida JDS; Junior GB; Aires KRT; Silva AC; Gattass M
IEEE J Biomed Health Inform; 2020 Dec; 24(12):3491-3498. PubMed ID: 32976110
[TBL] [Abstract][Full Text] [Related]
3. CASDES: A Computer-Aided System to Support Dry Eye Diagnosis Based on Tear Film Maps.
Remeseiro B; Mosquera A; Penedo MG
IEEE J Biomed Health Inform; 2016 May; 20(3):936-943. PubMed ID: 25850096
[TBL] [Abstract][Full Text] [Related]
4. Statistical comparison of classifiers applied to the interferential tear film lipid layer automatic classification.
Remeseiro B; Penas M; Mosquera A; Novo J; Penedo MG; Yebra-Pimentel E
Comput Math Methods Med; 2012; 2012():207315. PubMed ID: 22567040
[TBL] [Abstract][Full Text] [Related]
5. Functional Morphology of the Lipid Layer of the Tear Film.
Arita R; Fukuoka S; Morishige N
Cornea; 2017 Nov; 36 Suppl 1():S60-S66. PubMed ID: 28957980
[TBL] [Abstract][Full Text] [Related]
6. A method for the automated classification of benign and malignant masses on digital breast tomosynthesis images using machine learning and radiomic features.
Sakai A; Onishi Y; Matsui M; Adachi H; Teramoto A; Saito K; Fujita H
Radiol Phys Technol; 2020 Mar; 13(1):27-36. PubMed ID: 31686300
[TBL] [Abstract][Full Text] [Related]
7. Non-invasive methods of assessing the tear film.
Yokoi N; Komuro A
Exp Eye Res; 2004 Mar; 78(3):399-407. PubMed ID: 15106919
[TBL] [Abstract][Full Text] [Related]
8. An interferometric method for the dynamic evaluation of the tear film.
Szczesna DH; Kasprzak HT; Jaronski J; Rydz A; Stenevi U
Acta Ophthalmol Scand; 2007 Mar; 85(2):202-8. PubMed ID: 17305735
[TBL] [Abstract][Full Text] [Related]
9. A methodology for improving tear film lipid layer classification.
Remeseiro B; Bolon-Canedo V; Peteiro-Barral D; Alonso-Betanzos A; Guijarro-Berdiñas B; Mosquera A; Penedo MG; Sánchez-Maroño N
IEEE J Biomed Health Inform; 2014 Jul; 18(4):1485-93. PubMed ID: 25014945
[TBL] [Abstract][Full Text] [Related]
10. Predicting dry eye using noninvasive techniques of tear film surface assessment.
Szczesna DH; Alonso-Caneiro D; Iskander DR; Read SA; Collins MJ
Invest Ophthalmol Vis Sci; 2011 Feb; 52(2):751-6. PubMed ID: 20881295
[TBL] [Abstract][Full Text] [Related]
11. Robust estimation of tear film surface quality in lateral shearing interferometry.
Szczesna DH; Iskander DR
J Biomed Opt; 2009; 14(6):064039. PubMed ID: 20059277
[TBL] [Abstract][Full Text] [Related]
12. New Insights Into the Lipid Layer of the Tear Film and Meibomian Glands.
Arita R; Fukuoka S; Morishige N
Eye Contact Lens; 2017 Nov; 43(6):335-339. PubMed ID: 28410282
[TBL] [Abstract][Full Text] [Related]
13. Tear Interferometric Patterns Reflect Clinical Tear Dynamics in Dry Eye Patients.
Arita R; Morishige N; Fujii T; Fukuoka S; Chung JL; Seo KY; Itoh K
Invest Ophthalmol Vis Sci; 2016 Jul; 57(8):3928-34. PubMed ID: 27472080
[TBL] [Abstract][Full Text] [Related]
14. Random Forest Algorithm-Based Ultrasonic Image in the Diagnosis of Patients with Dry Eye Syndrome and Its Relationship with Tear Osmotic Pressure.
Jiang L; Sun S; Chen J; Sun Z
Comput Math Methods Med; 2022; 2022():9437468. PubMed ID: 35265174
[TBL] [Abstract][Full Text] [Related]
15. Examination of tear film smoothness on corneae after refractive surgeries using a noninvasive interferometric method.
Szczesna DH; Kulas Z; Kasprzak HT; Stenevi U
J Biomed Opt; 2009; 14(6):064029. PubMed ID: 20059267
[TBL] [Abstract][Full Text] [Related]
16. Evaluation of an automatic dry eye test using MCDM methods and rank correlation.
Peteiro-Barral D; Remeseiro B; Méndez R; Penedo MG
Med Biol Eng Comput; 2017 Apr; 55(4):527-536. PubMed ID: 27311605
[TBL] [Abstract][Full Text] [Related]
17. [Factors influencing the measurement of tear film lipid layer thickness with interferometry].
Finis D; Pischel N; Borrelli M; Schrader S; Geerling G
Klin Monbl Augenheilkd; 2014 Jun; 231(6):603-10. PubMed ID: 24940758
[TBL] [Abstract][Full Text] [Related]
18. Validation of a new objective method to assess lipid layer thickness without the need of an interferometer.
García-Marqués JV; Talens-Estarelles C; García-Lázaro S; Cerviño A
Graefes Arch Clin Exp Ophthalmol; 2022 Feb; 260(2):655-676. PubMed ID: 34487223
[TBL] [Abstract][Full Text] [Related]
19. Non-invasive and objective tear film breakup detection on interference color images using convolutional neural networks.
Kikukawa Y; Tanaka S; Kosugi T; Pflugfelder SC
PLoS One; 2023; 18(3):e0282973. PubMed ID: 36913382
[TBL] [Abstract][Full Text] [Related]
20. Tear film interferometry as a diagnostic tool for evaluating normal and dry-eye tear film.
Doane MG; Lee ME
Adv Exp Med Biol; 1998; 438():297-303. PubMed ID: 9634899
[No Abstract] [Full Text] [Related]
[Next] [New Search]