132 related articles for article (PubMed ID: 36939264)
1. Analyzing Mitochondrial Morphology Through Simulation Supervised Learning.
Punnakkal AR; Godtliebsen G; Somani A; Andres Acuna Maldonado S; Birna Birgisdottir Å; Prasad DK; Horsch A; Agarwal K
J Vis Exp; 2023 Mar; (193):. PubMed ID: 36939264
[TBL] [Abstract][Full Text] [Related]
2. MultiHeadGAN: A deep learning method for low contrast retinal pigment epithelium cell segmentation with fluorescent flatmount microscopy images.
Yu H; Wang F; Teodoro G; Nickerson J; Kong J
Comput Biol Med; 2022 Jul; 146():105596. PubMed ID: 35617723
[TBL] [Abstract][Full Text] [Related]
3. Machine learning-based 3D segmentation of mitochondria in polarized epithelial cells.
Hultgren NW; Zhou T; Williams DS
Mitochondrion; 2024 May; 76():101882. PubMed ID: 38599302
[TBL] [Abstract][Full Text] [Related]
4. Machine learning applications in cell image analysis.
Kan A
Immunol Cell Biol; 2017 Jul; 95(6):525-530. PubMed ID: 28294138
[TBL] [Abstract][Full Text] [Related]
5. Weakly supervised cell instance segmentation under various conditions.
Nishimura K; Wang C; Watanabe K; Fei Elmer Ker D; Bise R
Med Image Anal; 2021 Oct; 73():102182. PubMed ID: 34340103
[TBL] [Abstract][Full Text] [Related]
6. Fluorescent Neuronal Cells v2: multi-task, multi-format annotations for deep learning in microscopy.
Clissa L; Macaluso A; Morelli R; Occhinegro A; Piscitiello E; Taddei L; Luppi M; Amici R; Cerri M; Hitrec T; Rinaldi L; Zoccoli A
Sci Data; 2024 Feb; 11(1):184. PubMed ID: 38341463
[TBL] [Abstract][Full Text] [Related]
7. PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation.
Wang G; Luo X; Gu R; Yang S; Qu Y; Zhai S; Zhao Q; Li K; Zhang S
Comput Methods Programs Biomed; 2023 Apr; 231():107398. PubMed ID: 36773591
[TBL] [Abstract][Full Text] [Related]
8. Effectiveness of Semi-Supervised Active Learning in Automated Wound Image Segmentation.
Curti N; Merli Y; Zengarini C; Giampieri E; Merlotti A; Dall'Olio D; Marcelli E; Bianchi T; Castellani G
Int J Mol Sci; 2022 Dec; 24(1):. PubMed ID: 36614147
[TBL] [Abstract][Full Text] [Related]
9. Semi-supervised learning for automatic segmentation of the knee from MRI with convolutional neural networks.
Burton W; Myers C; Rullkoetter P
Comput Methods Programs Biomed; 2020 Jun; 189():105328. PubMed ID: 31958580
[TBL] [Abstract][Full Text] [Related]
10. An annotated fluorescence image dataset for training nuclear segmentation methods.
Kromp F; Bozsaky E; Rifatbegovic F; Fischer L; Ambros M; Berneder M; Weiss T; Lazic D; Dörr W; Hanbury A; Beiske K; Ambros PF; Ambros IM; Taschner-Mandl S
Sci Data; 2020 Aug; 7(1):262. PubMed ID: 32782410
[TBL] [Abstract][Full Text] [Related]
11. High-Throughput Image Analysis of Lipid-Droplet-Bound Mitochondria.
Miller N; Wolf D; Alsabeeh N; Mahdaviani K; Segawa M; Liesa M; Shirihai OS
Methods Mol Biol; 2021; 2276():285-303. PubMed ID: 34060050
[TBL] [Abstract][Full Text] [Related]
12. Using Sparse Patch Annotation for Tumor Segmentation in Histopathological Images.
Liu Y; He Q; Duan H; Shi H; Han A; He Y
Sensors (Basel); 2022 Aug; 22(16):. PubMed ID: 36015814
[TBL] [Abstract][Full Text] [Related]
13. Ultrasound carotid plaque segmentation via image reconstruction-based self-supervised learning with limited training labels.
Zhou R; Ou Y; Fang X; Azarpazhooh MR; Gan H; Ye Z; Spence JD; Xu X; Fenster A
Math Biosci Eng; 2023 Jan; 20(2):1617-1636. PubMed ID: 36899501
[TBL] [Abstract][Full Text] [Related]
14. Classifying changes in LN-18 glial cell morphology: a supervised machine learning approach to analyzing cell microscopy data via FIJI and WEKA.
Mbiki S; McClendon J; Alexander-Bryant A; Gilmore J
Med Biol Eng Comput; 2020 Jul; 58(7):1419-1430. PubMed ID: 32314170
[TBL] [Abstract][Full Text] [Related]
15. Ultrasound prostate segmentation based on multidirectional deeply supervised V-Net.
Lei Y; Tian S; He X; Wang T; Wang B; Patel P; Jani AB; Mao H; Curran WJ; Liu T; Yang X
Med Phys; 2019 Jul; 46(7):3194-3206. PubMed ID: 31074513
[TBL] [Abstract][Full Text] [Related]
16. A Cell Segmentation/Tracking Tool Based on Machine Learning.
Deter HS; Dies M; Cameron CC; Butzin NC; Buceta J
Methods Mol Biol; 2019; 2040():399-422. PubMed ID: 31432490
[TBL] [Abstract][Full Text] [Related]
17. Weighted average ensemble-based semantic segmentation in biological electron microscopy images.
Shaga Devan K; Kestler HA; Read C; Walther P
Histochem Cell Biol; 2022 Nov; 158(5):447-462. PubMed ID: 35988009
[TBL] [Abstract][Full Text] [Related]
18. Semi-Supervised Neuron Segmentation via Reinforced Consistency Learning.
Huang W; Chen C; Xiong Z; Zhang Y; Chen X; Sun X; Wu F
IEEE Trans Med Imaging; 2022 Nov; 41(11):3016-3028. PubMed ID: 35584076
[TBL] [Abstract][Full Text] [Related]
19. Automated left ventricular myocardium segmentation using 3D deeply supervised attention U-net for coronary computed tomography angiography; CT myocardium segmentation.
Jun Guo B; He X; Lei Y; Harms J; Wang T; Curran WJ; Liu T; Jiang Zhang L; Yang X
Med Phys; 2020 Apr; 47(4):1775-1785. PubMed ID: 32017118
[TBL] [Abstract][Full Text] [Related]
20. A dual autoencoder and singular value decomposition based feature optimization for the segmentation of brain tumor from MRI images.
Aswani K; Menaka D
BMC Med Imaging; 2021 May; 21(1):82. PubMed ID: 33985449
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
