299 related articles for article (PubMed ID: 33602101)
1. A Simplified Framework for the Detection of Intracranial Hemorrhage in CT Brain Images Using Deep Learning.
Kumaravel P; Mohan S; Arivudaiyanambi J; Shajil N; Venkatakrishnan HN
Curr Med Imaging; 2021; 17(10):1226-1236. PubMed ID: 33602101
[TBL] [Abstract][Full Text] [Related]
2. Application of Deep Learning in Neuroradiology: Brain Haemorrhage Classification Using Transfer Learning.
Dawud AM; Yurtkan K; Oztoprak H
Comput Intell Neurosci; 2019; 2019():4629859. PubMed ID: 31281335
[TBL] [Abstract][Full Text] [Related]
3. Fully automated sinogram-based deep learning model for detection and classification of intracranial hemorrhage.
Sindhura C; Al Fahim M; Yalavarthy PK; Gorthi S
Med Phys; 2024 Mar; 51(3):1944-1956. PubMed ID: 37702932
[TBL] [Abstract][Full Text] [Related]
4. Examination-Level Supervision for Deep Learning-based Intracranial Hemorrhage Detection on Head CT Scans.
Teneggi J; Yi PH; Sulam J
Radiol Artif Intell; 2024 Jan; 6(1):e230159. PubMed ID: 38294324
[TBL] [Abstract][Full Text] [Related]
5. Deep Gaussian processes for multiple instance learning: Application to CT intracranial hemorrhage detection.
López-Pérez M; Schmidt A; Wu Y; Molina R; Katsaggelos AK
Comput Methods Programs Biomed; 2022 Jun; 219():106783. PubMed ID: 35390723
[TBL] [Abstract][Full Text] [Related]
6. Detection and classification of intracranial haemorrhage on CT images using a novel deep-learning algorithm.
Lee JY; Kim JS; Kim TY; Kim YS
Sci Rep; 2020 Nov; 10(1):20546. PubMed ID: 33239711
[TBL] [Abstract][Full Text] [Related]
7. Accurate and Efficient Intracranial Hemorrhage Detection and Subtype Classification in 3D CT Scans with Convolutional and Long Short-Term Memory Neural Networks.
Burduja M; Ionescu RT; Verga N
Sensors (Basel); 2020 Oct; 20(19):. PubMed ID: 33019508
[TBL] [Abstract][Full Text] [Related]
8. Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network.
Ye H; Gao F; Yin Y; Guo D; Zhao P; Lu Y; Wang X; Bai J; Cao K; Song Q; Zhang H; Chen W; Guo X; Xia J
Eur Radiol; 2019 Nov; 29(11):6191-6201. PubMed ID: 31041565
[TBL] [Abstract][Full Text] [Related]
9. A deep learning algorithm for automatic detection and classification of acute intracranial hemorrhages in head CT scans.
Wang X; Shen T; Yang S; Lan J; Xu Y; Wang M; Zhang J; Han X
Neuroimage Clin; 2021; 32():102785. PubMed ID: 34411910
[TBL] [Abstract][Full Text] [Related]
10. Feasible Study on Intracranial Hemorrhage Detection and Classification using a CNN-LSTM Network.
Ko H; Chung H; Lee H; Lee J
Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():1290-1293. PubMed ID: 33018224
[TBL] [Abstract][Full Text] [Related]
11. Computer aid screening of COVID-19 using X-ray and CT scan images: An inner comparison.
Sethy PK; Behera SK; Anitha K; Pandey C; Khan MR
J Xray Sci Technol; 2021; 29(2):197-210. PubMed ID: 33492267
[TBL] [Abstract][Full Text] [Related]
12. Improving Sensitivity on Identification and Delineation of Intracranial Hemorrhage Lesion Using Cascaded Deep Learning Models.
Cho J; Park KS; Karki M; Lee E; Ko S; Kim JK; Lee D; Choe J; Son J; Kim M; Lee S; Lee J; Yoon C; Park S
J Digit Imaging; 2019 Jun; 32(3):450-461. PubMed ID: 30680471
[TBL] [Abstract][Full Text] [Related]
13. Classification of Intracranial Hemorrhage Subtypes Using Deep Learning on CT Scans.
Danilov G; Kotik K; Negreeva A; Tsukanova T; Shifrin M; Zakharova N; Batalov A; Pronin I; Potapov A
Stud Health Technol Inform; 2020 Jun; 272():370-373. PubMed ID: 32604679
[TBL] [Abstract][Full Text] [Related]
14. Brain Magnetic Resonance Imaging Classification Using Deep Learning Architectures with Gender and Age.
Wahlang I; Maji AK; Saha G; Chakrabarti P; Jasinski M; Leonowicz Z; Jasinska E
Sensors (Basel); 2022 Feb; 22(5):. PubMed ID: 35270913
[TBL] [Abstract][Full Text] [Related]
15. A deep learning framework for automatic detection of arbitrarily shaped fiducial markers in intrafraction fluoroscopic images.
Mylonas A; Keall PJ; Booth JT; Shieh CC; Eade T; Poulsen PR; Nguyen DT
Med Phys; 2019 May; 46(5):2286-2297. PubMed ID: 30929254
[TBL] [Abstract][Full Text] [Related]
16. Evaluation of techniques to improve a deep learning algorithm for the automatic detection of intracranial haemorrhage on CT head imaging.
Yeo M; Tahayori B; Kok HK; Maingard J; Kutaiba N; Russell J; Thijs V; Jhamb A; Chandra RV; Brooks M; Barras CD; Asadi H
Eur Radiol Exp; 2023 Apr; 7(1):17. PubMed ID: 37032417
[TBL] [Abstract][Full Text] [Related]
17. Automated Computer-Aided Detection and Classification of Intracranial Hemorrhage Using Ensemble Deep Learning Techniques.
Umapathy S; Murugappan M; Bharathi D; Thakur M
Diagnostics (Basel); 2023 Sep; 13(18):. PubMed ID: 37761354
[TBL] [Abstract][Full Text] [Related]
18. A comparison of performance between a deep learning model with residents for localization and classification of intracranial hemorrhage.
Angkurawaranon S; Sanorsieng N; Unsrisong K; Inkeaw P; Sripan P; Khumrin P; Angkurawaranon C; Vaniyapong T; Chitapanarux I
Sci Rep; 2023 Jun; 13(1):9975. PubMed ID: 37340038
[TBL] [Abstract][Full Text] [Related]
19. Deep feature classification of angiomyolipoma without visible fat and renal cell carcinoma in abdominal contrast-enhanced CT images with texture image patches and hand-crafted feature concatenation.
Lee H; Hong H; Kim J; Jung DC
Med Phys; 2018 Apr; 45(4):1550-1561. PubMed ID: 29474742
[TBL] [Abstract][Full Text] [Related]
20. Text Analysis of Radiology Reports with Signs of Intracranial Hemorrhage on Brain CT Scans Using the Decision Tree Algorithm.
Khoruzhaya АN; Kozlov DV; Arzamasov КM; Kremneva EI
Sovrem Tekhnologii Med; 2022; 14(6):34-40. PubMed ID: 37181285
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
