156 related articles for article (PubMed ID: 36276999)
1. MSeg-Net: A Melanoma Mole Segmentation Network Using CornerNet and Fuzzy
Nawaz M; Nazir T; Khan MA; Alhaisoni M; Kim JY; Nam Y
Comput Math Methods Med; 2022; 2022():7502504. PubMed ID: 36276999
[TBL] [Abstract][Full Text] [Related]
2. Skin cancer detection from dermoscopic images using deep learning and fuzzy k-means clustering.
Nawaz M; Mehmood Z; Nazir T; Naqvi RA; Rehman A; Iqbal M; Saba T
Microsc Res Tech; 2022 Jan; 85(1):339-351. PubMed ID: 34448519
[TBL] [Abstract][Full Text] [Related]
3. Efficient skin lesion segmentation using separable-Unet with stochastic weight averaging.
Tang P; Liang Q; Yan X; Xiang S; Sun W; Zhang D; Coppola G
Comput Methods Programs Biomed; 2019 Sep; 178():289-301. PubMed ID: 31416556
[TBL] [Abstract][Full Text] [Related]
4. Automatic lesion segmentation using atrous convolutional deep neural networks in dermoscopic skin cancer images.
Kaur R; GholamHosseini H; Sinha R; Lindén M
BMC Med Imaging; 2022 May; 22(1):103. PubMed ID: 35644612
[TBL] [Abstract][Full Text] [Related]
5. Melanoma lesion detection and segmentation using deep region based convolutional neural network and fuzzy C-means clustering.
Nida N; Irtaza A; Javed A; Yousaf MH; Mahmood MT
Int J Med Inform; 2019 Apr; 124():37-48. PubMed ID: 30784425
[TBL] [Abstract][Full Text] [Related]
6. Melanoma segmentation using deep learning with test-time augmentations and conditional random fields.
Ashraf H; Waris A; Ghafoor MF; Gilani SO; Niazi IK
Sci Rep; 2022 Mar; 12(1):3948. PubMed ID: 35273282
[TBL] [Abstract][Full Text] [Related]
7. Segmentation of skin lesions in dermoscopy images using fuzzy classification of pixels and histogram thresholding.
Garcia-Arroyo JL; Garcia-Zapirain B
Comput Methods Programs Biomed; 2019 Jan; 168():11-19. PubMed ID: 30527129
[TBL] [Abstract][Full Text] [Related]
8. Dynamically aggregating MLPs and CNNs for skin lesion segmentation with geometry regularization.
Qin C; Zheng B; Zeng J; Chen Z; Zhai Y; Genovese A; Piuri V; Scotti F
Comput Methods Programs Biomed; 2023 Aug; 238():107601. PubMed ID: 37210926
[TBL] [Abstract][Full Text] [Related]
9. Skin lesion segmentation in dermoscopy images via deep full resolution convolutional networks.
Al-Masni MA; Al-Antari MA; Choi MT; Han SM; Kim TS
Comput Methods Programs Biomed; 2018 Aug; 162():221-231. PubMed ID: 29903489
[TBL] [Abstract][Full Text] [Related]
10. Automated Detection of Nonmelanoma Skin Cancer Based on Deep Convolutional Neural Network.
Arif M; Philip FM; Ajesh F; Izdrui D; Craciun MD; Geman O
J Healthc Eng; 2022; 2022():6952304. PubMed ID: 35186235
[TBL] [Abstract][Full Text] [Related]
11. Melanoma recognition in dermoscopy images using lesion's peripheral region information.
Tajeddin NZ; Asl BM
Comput Methods Programs Biomed; 2018 Sep; 163():143-153. PubMed ID: 30119849
[TBL] [Abstract][Full Text] [Related]
12. Segmentation of dermatoscopic images by frequency domain filtering and k-means clustering algorithms.
Rajab MI
Skin Res Technol; 2011 Nov; 17(4):469-78. PubMed ID: 21342295
[TBL] [Abstract][Full Text] [Related]
13. Developing a Recognition System for Diagnosing Melanoma Skin Lesions Using Artificial Intelligence Algorithms.
Alsaade FW; Aldhyani THH; Al-Adhaileh MH
Comput Math Methods Med; 2021; 2021():9998379. PubMed ID: 34055044
[TBL] [Abstract][Full Text] [Related]
14. Detecting anomalous growth of skin lesion using threshold-based segmentation algorithm and Fuzzy K-Nearest Neighbor classifier.
Sivaraj S; Malmathanraj R; Palanisamy P
J Cancer Res Ther; 2020; 16(1):40-52. PubMed ID: 32362608
[TBL] [Abstract][Full Text] [Related]
15. Digital hair segmentation using hybrid convolutional and recurrent neural networks architecture.
Attia M; Hossny M; Zhou H; Nahavandi S; Asadi H; Yazdabadi A
Comput Methods Programs Biomed; 2019 Aug; 177():17-30. PubMed ID: 31319945
[TBL] [Abstract][Full Text] [Related]
16. Skin Lesion Segmentation from Dermoscopic Images Using Convolutional Neural Network.
Zafar K; Gilani SO; Waris A; Ahmed A; Jamil M; Khan MN; Sohail Kashif A
Sensors (Basel); 2020 Mar; 20(6):. PubMed ID: 32183041
[TBL] [Abstract][Full Text] [Related]
17. Segmentation of dermoscopy images based on deformable 3D convolution and ResU-NeXt +.
Zhao C; Shuai R; Ma L; Liu W; Wu M
Med Biol Eng Comput; 2021 Sep; 59(9):1815-1832. PubMed ID: 34304370
[TBL] [Abstract][Full Text] [Related]
18. Dermoscopic Image Segmentation via Multistage Fully Convolutional Networks.
Bi L; Kim J; Ahn E; Kumar A; Fulham M; Feng D
IEEE Trans Biomed Eng; 2017 Sep; 64(9):2065-2074. PubMed ID: 28600236
[TBL] [Abstract][Full Text] [Related]
19. DSNet: Automatic dermoscopic skin lesion segmentation.
Hasan MK; Dahal L; Samarakoon PN; Tushar FI; Martí R
Comput Biol Med; 2020 May; 120():103738. PubMed ID: 32421644
[TBL] [Abstract][Full Text] [Related]
20. Construction of saliency map and hybrid set of features for efficient segmentation and classification of skin lesion.
Khan MA; Akram T; Sharif M; Saba T; Javed K; Lali IU; Tanik UJ; Rehman A
Microsc Res Tech; 2019 Jun; 82(6):741-763. PubMed ID: 30768826
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]