139 related articles for article (PubMed ID: 33817018)
1. Performance analysis of lightweight CNN models to segment infectious lung tissues of COVID-19 cases from tomographic images.
Iyer TJ; Joseph Raj AN; Ghildiyal S; Nersisson R
PeerJ Comput Sci; 2021; 7():e368. PubMed ID: 33817018
[TBL] [Abstract][Full Text] [Related]
2. Automated deep learning-based segmentation of COVID-19 lesions from chest computed tomography images.
Salehi M; Ardekani MA; Taramsari AB; Ghaffari H; Haghparast M
Pol J Radiol; 2022; 87():e478-e486. PubMed ID: 36091652
[TBL] [Abstract][Full Text] [Related]
3. MID-UNet: Multi-input directional UNet for COVID-19 lung infection segmentation from CT images.
Chi J; Zhang S; Han X; Wang H; Wu C; Yu X
Signal Process Image Commun; 2022 Oct; 108():116835. PubMed ID: 35935468
[TBL] [Abstract][Full Text] [Related]
4. CARes-UNet: Content-aware residual UNet for lesion segmentation of COVID-19 from chest CT images.
Xu X; Wen Y; Zhao L; Zhang Y; Zhao Y; Tang Z; Yang Z; Chen CY
Med Phys; 2021 Nov; 48(11):7127-7140. PubMed ID: 34528263
[TBL] [Abstract][Full Text] [Related]
5. Application of convolutional neural networks towards nuclei segmentation in localization-based super-resolution fluorescence microscopy images.
Mela CA; Liu Y
BMC Bioinformatics; 2021 Jun; 22(1):325. PubMed ID: 34130628
[TBL] [Abstract][Full Text] [Related]
6. Dense-UNet: a novel multiphoton
Cai S; Tian Y; Lui H; Zeng H; Wu Y; Chen G
Quant Imaging Med Surg; 2020 Jun; 10(6):1275-1285. PubMed ID: 32550136
[TBL] [Abstract][Full Text] [Related]
7. Anam-Net: Anamorphic Depth Embedding-Based Lightweight CNN for Segmentation of Anomalies in COVID-19 Chest CT Images.
Paluru N; Dayal A; Jenssen HB; Sakinis T; Cenkeramaddi LR; Prakash J; Yalavarthy PK
IEEE Trans Neural Netw Learn Syst; 2021 Mar; 32(3):932-946. PubMed ID: 33544680
[TBL] [Abstract][Full Text] [Related]
8. Segmenting lung lesions of COVID-19 from CT images via pyramid pooling improved Unet.
Ma Y; Feng P; He P; Ren Y; Guo X; Yu X; Wei B
Biomed Phys Eng Express; 2021 May; 7(4):. PubMed ID: 33979791
[TBL] [Abstract][Full Text] [Related]
9. Adaptive UNet-based Lung Segmentation and Ensemble Learning with CNN-based Deep Features for Automated COVID-19 Diagnosis.
Das A
Multimed Tools Appl; 2022; 81(4):5407-5441. PubMed ID: 34955679
[TBL] [Abstract][Full Text] [Related]
10. Efficient deep neural networks for classification of COVID-19 based on CT images: Virtualization via software defined radio.
Fouladi S; Ebadi MJ; Safaei AA; Bajuri MY; Ahmadian A
Comput Commun; 2021 Aug; 176():234-248. PubMed ID: 34149118
[TBL] [Abstract][Full Text] [Related]
11. Decoders configurations based on Unet family and feature pyramid network for COVID-19 segmentation on CT images.
Nguyen HT; Bao Tran T; Luong HH; Nguyen Huynh TK
PeerJ Comput Sci; 2021; 7():e719. PubMed ID: 34616895
[TBL] [Abstract][Full Text] [Related]
12. Lung tumor segmentation in 4D CT images using motion convolutional neural networks.
Momin S; Lei Y; Tian Z; Wang T; Roper J; Kesarwala AH; Higgins K; Bradley JD; Liu T; Yang X
Med Phys; 2021 Nov; 48(11):7141-7153. PubMed ID: 34469001
[TBL] [Abstract][Full Text] [Related]
13. A novel adaptive cubic quasi-Newton optimizer for deep learning based medical image analysis tasks, validated on detection of COVID-19 and segmentation for COVID-19 lung infection, liver tumor, and optic disc/cup.
Liu Y; Zhang M; Zhong Z; Zeng X
Med Phys; 2023 Mar; 50(3):1528-1538. PubMed ID: 36057788
[TBL] [Abstract][Full Text] [Related]
14. COVID TV-Unet: Segmenting COVID-19 chest CT images using connectivity imposed Unet.
Saeedizadeh N; Minaee S; Kafieh R; Yazdani S; Sonka M
Comput Methods Programs Biomed Update; 2021; 1():100007. PubMed ID: 34337587
[TBL] [Abstract][Full Text] [Related]
15. Automatic segmentation and applicator reconstruction for CT-based brachytherapy of cervical cancer using 3D convolutional neural networks.
Zhang D; Yang Z; Jiang S; Zhou Z; Meng M; Wang W
J Appl Clin Med Phys; 2020 Oct; 21(10):158-169. PubMed ID: 32991783
[TBL] [Abstract][Full Text] [Related]
16. Attention-enabled 3D boosted convolutional neural networks for semantic CT segmentation using deep supervision.
Kearney V; Chan JW; Wang T; Perry A; Yom SS; Solberg TD
Phys Med Biol; 2019 Jul; 64(13):135001. PubMed ID: 31181561
[TBL] [Abstract][Full Text] [Related]
17. Enhancing COVID-19 CT Image Segmentation: A Comparative Study of Attention and Recurrence in UNet Models.
Buongiorno R; Del Corso G; Germanese D; Colligiani L; Python L; Romei C; Colantonio S
J Imaging; 2023 Dec; 9(12):. PubMed ID: 38132701
[TBL] [Abstract][Full Text] [Related]
18. CoLe-CNN+: Context learning - Convolutional neural network for COVID-19-Ground-Glass-Opacities detection and segmentation.
Pezzano G; Díaz O; Ripoll VR; Radeva P
Comput Biol Med; 2021 Sep; 136():104689. PubMed ID: 34364263
[TBL] [Abstract][Full Text] [Related]
19. Mandible segmentation from CT data for virtual surgical planning using an augmented two-stepped convolutional neural network.
Pankert T; Lee H; Peters F; Hölzle F; Modabber A; Raith S
Int J Comput Assist Radiol Surg; 2023 Aug; 18(8):1479-1488. PubMed ID: 36637748
[TBL] [Abstract][Full Text] [Related]
20. MMViT-Seg: A lightweight transformer and CNN fusion network for COVID-19 segmentation.
Yang Y; Zhang L; Ren L; Wang X
Comput Methods Programs Biomed; 2023 Mar; 230():107348. PubMed ID: 36706618
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]