317 related articles for article (PubMed ID: 34601391)
1. Deep multiple-instance learning for abnormal cell detection in cervical histopathology images.
Pal A; Xue Z; Desai K; Aina F Banjo A; Adepiti CA; Long LR; Schiffman M; Antani S
Comput Biol Med; 2021 Nov; 138():104890. PubMed ID: 34601391
[TBL] [Abstract][Full Text] [Related]
2. A review of image analysis and machine learning techniques for automated cervical cancer screening from pap-smear images.
William W; Ware A; Basaza-Ejiri AH; Obungoloch J
Comput Methods Programs Biomed; 2018 Oct; 164():15-22. PubMed ID: 30195423
[TBL] [Abstract][Full Text] [Related]
3. A Cervical Histopathology Dataset for Computer Aided Diagnosis of Precancerous Lesions.
Meng Z; Zhao Z; Li B; Su F; Guo L
IEEE Trans Med Imaging; 2021 Jun; 40(6):1531-1541. PubMed ID: 33600310
[TBL] [Abstract][Full Text] [Related]
4. Mitosis detection in breast cancer histological images An ICPR 2012 contest.
Roux L; Racoceanu D; Loménie N; Kulikova M; Irshad H; Klossa J; Capron F; Genestie C; Le Naour G; Gurcan MN
J Pathol Inform; 2013; 4():8. PubMed ID: 23858383
[TBL] [Abstract][Full Text] [Related]
5. TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma.
Sun X; Li W; Fu B; Peng Y; He J; Wang L; Yang T; Meng X; Li J; Wang J; Huang P; Wang R
Comput Methods Programs Biomed; 2023 Dec; 242():107789. PubMed ID: 37722310
[TBL] [Abstract][Full Text] [Related]
6. Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.
Ehteshami Bejnordi B; Veta M; Johannes van Diest P; van Ginneken B; Karssemeijer N; Litjens G; van der Laak JAWM; ; Hermsen M; Manson QF; Balkenhol M; Geessink O; Stathonikos N; van Dijk MC; Bult P; Beca F; Beck AH; Wang D; Khosla A; Gargeya R; Irshad H; Zhong A; Dou Q; Li Q; Chen H; Lin HJ; Heng PA; Haß C; Bruni E; Wong Q; Halici U; Öner MÜ; Cetin-Atalay R; Berseth M; Khvatkov V; Vylegzhanin A; Kraus O; Shaban M; Rajpoot N; Awan R; Sirinukunwattana K; Qaiser T; Tsang YW; Tellez D; Annuscheit J; Hufnagl P; Valkonen M; Kartasalo K; Latonen L; Ruusuvuori P; Liimatainen K; Albarqouni S; Mungal B; George A; Demirci S; Navab N; Watanabe S; Seno S; Takenaka Y; Matsuda H; Ahmady Phoulady H; Kovalev V; Kalinovsky A; Liauchuk V; Bueno G; Fernandez-Carrobles MM; Serrano I; Deniz O; Racoceanu D; Venâncio R
JAMA; 2017 Dec; 318(22):2199-2210. PubMed ID: 29234806
[TBL] [Abstract][Full Text] [Related]
7. Point-of-care mobile digital microscopy and deep learning for the detection of soil-transmitted helminths and Schistosoma haematobium.
Holmström O; Linder N; Ngasala B; Mårtensson A; Linder E; Lundin M; Moilanen H; Suutala A; Diwan V; Lundin J
Glob Health Action; 2017 Jun; 10(sup3):1337325. PubMed ID: 28838305
[TBL] [Abstract][Full Text] [Related]
8. Ensemble Deep Learning for Cervix Image Selection toward Improving Reliability in Automated Cervical Precancer Screening.
Guo P; Xue Z; Mtema Z; Yeates K; Ginsburg O; Demarco M; Long LR; Schiffman M; Antani S
Diagnostics (Basel); 2020 Jul; 10(7):. PubMed ID: 32635269
[TBL] [Abstract][Full Text] [Related]
9. A pap-smear analysis tool (PAT) for detection of cervical cancer from pap-smear images.
William W; Ware A; Basaza-Ejiri AH; Obungoloch J
Biomed Eng Online; 2019 Feb; 18(1):16. PubMed ID: 30755214
[TBL] [Abstract][Full Text] [Related]
10. A screening assistance system for cervical cytology of squamous cell atypia based on a two-step combined CNN algorithm with label smoothing.
Nambu Y; Mariya T; Shinkai S; Umemoto M; Asanuma H; Sato I; Hirohashi Y; Torigoe T; Fujino Y; Saito T
Cancer Med; 2022 Jan; 11(2):520-529. PubMed ID: 34841722
[TBL] [Abstract][Full Text] [Related]
11. Multi-Instance Multi-Label Learning for Multi-Class Classification of Whole Slide Breast Histopathology Images.
Mercan C; Aksoy S; Mercan E; Shapiro LG; Weaver DL; Elmore JG
IEEE Trans Med Imaging; 2018 Jan; 37(1):316-325. PubMed ID: 28981408
[TBL] [Abstract][Full Text] [Related]
12. AF-SENet: Classification of Cancer in Cervical Tissue Pathological Images Based on Fusing Deep Convolution Features.
Huang P; Tan X; Chen C; Lv X; Li Y
Sensors (Basel); 2020 Dec; 21(1):. PubMed ID: 33375508
[TBL] [Abstract][Full Text] [Related]
13. Comparison of glass slides and various digital-slide modalities for cytopathology screening and interpretation.
Hanna MG; Monaco SE; Cuda J; Xing J; Ahmed I; Pantanowitz L
Cancer Cytopathol; 2017 Sep; 125(9):701-709. PubMed ID: 28558124
[TBL] [Abstract][Full Text] [Related]
14. Accurate deep learning model using semi-supervised learning and Noisy Student for cervical cancer screening in low magnification images.
Kurita Y; Meguro S; Tsuyama N; Kosugi I; Enomoto Y; Kawasaki H; Uemura T; Kimura M; Iwashita T
PLoS One; 2023; 18(5):e0285996. PubMed ID: 37200281
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. A multi-resolution model for histopathology image classification and localization with multiple instance learning.
Li J; Li W; Sisk A; Ye H; Wallace WD; Speier W; Arnold CW
Comput Biol Med; 2021 Apr; 131():104253. PubMed ID: 33601084
[TBL] [Abstract][Full Text] [Related]
17. Deep Convolution Neural Network for Malignancy Detection and Classification in Microscopic Uterine Cervix Cell Images.
P B S; Faruqi F; K S H; Kudva R
Asian Pac J Cancer Prev; 2019 Nov; 20(11):3447-3456. PubMed ID: 31759371
[TBL] [Abstract][Full Text] [Related]
18. A demonstration of automated visual evaluation of cervical images taken with a smartphone camera.
Xue Z; Novetsky AP; Einstein MH; Marcus JZ; Befano B; Guo P; Demarco M; Wentzensen N; Long LR; Schiffman M; Antani S
Int J Cancer; 2020 Nov; 147(9):2416-2423. PubMed ID: 32356305
[TBL] [Abstract][Full Text] [Related]
19. Use of Deep Learning to Develop and Analyze Computational Hematoxylin and Eosin Staining of Prostate Core Biopsy Images for Tumor Diagnosis.
Rana A; Lowe A; Lithgow M; Horback K; Janovitz T; Da Silva A; Tsai H; Shanmugam V; Bayat A; Shah P
JAMA Netw Open; 2020 May; 3(5):e205111. PubMed ID: 32432709
[TBL] [Abstract][Full Text] [Related]
20. An Evaluation of Computational Learning-based Methods for the Segmentation of Nuclei in Cervical Cancer Cells from Microscopic Images.
Maylaa T; Windal F; Benhabiles H; Maubon G; Maubon N; Vandenhaute E; Collard D
Curr Comput Aided Drug Des; 2022; 18(2):81-94. PubMed ID: 35139795
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
