579 related articles for article (PubMed ID: 29813023)
1. Wavelet-enhanced convolutional neural network: a new idea in a deep learning paradigm.
Savareh BA; Emami H; Hajiabadi M; Azimi SM; Ghafoori M
Biomed Tech (Berl); 2019 Apr; 64(2):195-205. PubMed ID: 29813023
[TBL] [Abstract][Full Text] [Related]
2. Comparison of wavelet transformations to enhance convolutional neural network performance in brain tumor segmentation.
Hajiabadi M; Alizadeh Savareh B; Emami H; Bashiri A
BMC Med Inform Decis Mak; 2021 Nov; 21(1):327. PubMed ID: 34814907
[TBL] [Abstract][Full Text] [Related]
3. A Novel Method for Classifying Liver and Brain Tumors Using Convolutional Neural Networks, Discrete Wavelet Transform and Long Short-Term Memory Networks.
Kutlu H; Avcı E
Sensors (Basel); 2019 Apr; 19(9):. PubMed ID: 31035406
[TBL] [Abstract][Full Text] [Related]
4. DENSE-INception U-net for medical image segmentation.
Zhang Z; Wu C; Coleman S; Kerr D
Comput Methods Programs Biomed; 2020 Aug; 192():105395. PubMed ID: 32163817
[TBL] [Abstract][Full Text] [Related]
5. An Intelligent Diagnosis Method of Brain MRI Tumor Segmentation Using Deep Convolutional Neural Network and SVM Algorithm.
Wu W; Li D; Du J; Gao X; Gu W; Zhao F; Feng X; Yan H
Comput Math Methods Med; 2020; 2020():6789306. PubMed ID: 32733596
[TBL] [Abstract][Full Text] [Related]
6. Automatic PET cervical tumor segmentation by combining deep learning and anatomic prior.
Chen L; Shen C; Zhou Z; Maquilan G; Albuquerque K; Folkert MR; Wang J
Phys Med Biol; 2019 Apr; 64(8):085019. PubMed ID: 30818303
[TBL] [Abstract][Full Text] [Related]
7. A comparative study of pre-trained convolutional neural networks for semantic segmentation of breast tumors in ultrasound.
Gómez-Flores W; Coelho de Albuquerque Pereira W
Comput Biol Med; 2020 Nov; 126():104036. PubMed ID: 33059238
[TBL] [Abstract][Full Text] [Related]
8. A new approach for brain tumor diagnosis system: Single image super resolution based maximum fuzzy entropy segmentation and convolutional neural network.
Sert E; Özyurt F; Doğantekin A
Med Hypotheses; 2019 Dec; 133():109413. PubMed ID: 31586812
[TBL] [Abstract][Full Text] [Related]
9. DeepNAT: Deep convolutional neural network for segmenting neuroanatomy.
Wachinger C; Reuter M; Klein T
Neuroimage; 2018 Apr; 170():434-445. PubMed ID: 28223187
[TBL] [Abstract][Full Text] [Related]
10. Utilizing wavelet deep learning network to classify different states of task-fMRI for verifying activation regions.
Gui S; Gui R
Int J Neurosci; 2020 Jun; 130(6):583-594. PubMed ID: 31778088
[No Abstract] [Full Text] [Related]
11. Segmentation of white matter hyperintensities using convolutional neural networks with global spatial information in routine clinical brain MRI with none or mild vascular pathology.
Rachmadi MF; Valdés-Hernández MDC; Agan MLF; Di Perri C; Komura T;
Comput Med Imaging Graph; 2018 Jun; 66():28-43. PubMed ID: 29523002
[TBL] [Abstract][Full Text] [Related]
12. An efficient brain tumor image classifier by combining multi-pathway cascaded deep neural network and handcrafted features in MR images.
Bal A; Banerjee M; Chaki R; Sharma P
Med Biol Eng Comput; 2021 Aug; 59(7-8):1495-1527. PubMed ID: 34184181
[TBL] [Abstract][Full Text] [Related]
13. Context aware deep learning for brain tumor segmentation, subtype classification, and survival prediction using radiology images.
Pei L; Vidyaratne L; Rahman MM; Iftekharuddin KM
Sci Rep; 2020 Nov; 10(1):19726. PubMed ID: 33184301
[TBL] [Abstract][Full Text] [Related]
14. Brain tumor segmentation with Deep Neural Networks.
Havaei M; Davy A; Warde-Farley D; Biard A; Courville A; Bengio Y; Pal C; Jodoin PM; Larochelle H
Med Image Anal; 2017 Jan; 35():18-31. PubMed ID: 27310171
[TBL] [Abstract][Full Text] [Related]
15. A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstruction.
Kang E; Min J; Ye JC
Med Phys; 2017 Oct; 44(10):e360-e375. PubMed ID: 29027238
[TBL] [Abstract][Full Text] [Related]
16. Automatic recognition of holistic functional brain networks using iteratively optimized convolutional neural networks (IO-CNN) with weak label initialization.
Zhao Y; Ge F; Liu T
Med Image Anal; 2018 Jul; 47():111-126. PubMed ID: 29705574
[TBL] [Abstract][Full Text] [Related]
17. An Efficient Implementation of Deep Convolutional Neural Networks for MRI Segmentation.
Hoseini F; Shahbahrami A; Bayat P
J Digit Imaging; 2018 Oct; 31(5):738-747. PubMed ID: 29488179
[TBL] [Abstract][Full Text] [Related]
18. A convolutional neural network algorithm for automatic segmentation of head and neck organs at risk using deep lifelong learning.
Chan JW; Kearney V; Haaf S; Wu S; Bogdanov M; Reddick M; Dixit N; Sudhyadhom A; Chen J; Yom SS; Solberg TD
Med Phys; 2019 May; 46(5):2204-2213. PubMed ID: 30887523
[TBL] [Abstract][Full Text] [Related]
19. Practical method of cell segmentation in electron microscope image stack using deep convolutional neural network☆.
Konishi K; Mimura M; Nonaka T; Sase I; Nishioka H; Suga M
Microscopy (Oxf); 2019 Aug; 68(4):338-341. PubMed ID: 31220299
[TBL] [Abstract][Full Text] [Related]
20. Comparison of Deep-Learning and Conventional Machine-Learning Methods for the Automatic Recognition of the Hepatocellular Carcinoma Areas from Ultrasound Images.
Brehar R; Mitrea DA; Vancea F; Marita T; Nedevschi S; Lupsor-Platon M; Rotaru M; Badea RI
Sensors (Basel); 2020 May; 20(11):. PubMed ID: 32485986
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
