176 related articles for article (PubMed ID: 35691144)
1. Boundary-rendering network for breast lesion segmentation in ultrasound images.
Huang R; Lin M; Dou H; Lin Z; Ying Q; Jia X; Xu W; Mei Z; Yang X; Dong Y; Zhou J; Ni D
Med Image Anal; 2022 Aug; 80():102478. PubMed ID: 35691144
[TBL] [Abstract][Full Text] [Related]
2. Boundary-Guided and Region-Aware Network With Global Scale-Adaptive for Accurate Segmentation of Breast Tumors in Ultrasound Images.
Hu K; Zhang X; Lee D; Xiong D; Zhang Y; Gao X
IEEE J Biomed Health Inform; 2023 Sep; 27(9):4421-4432. PubMed ID: 37310830
[TBL] [Abstract][Full Text] [Related]
3. Semi-supervised segmentation of lesion from breast ultrasound images with attentional generative adversarial network.
Han L; Huang Y; Dou H; Wang S; Ahamad S; Luo H; Liu Q; Fan J; Zhang J
Comput Methods Programs Biomed; 2020 Jun; 189():105275. PubMed ID: 31978805
[TBL] [Abstract][Full Text] [Related]
4. Automatic tumor segmentation in breast ultrasound images using a dilated fully convolutional network combined with an active contour model.
Hu Y; Guo Y; Wang Y; Yu J; Li J; Zhou S; Chang C
Med Phys; 2019 Jan; 46(1):215-228. PubMed ID: 30374980
[TBL] [Abstract][Full Text] [Related]
5. Breast ultrasound image segmentation: A coarse-to-fine fusion convolutional neural network.
Wang K; Liang S; Zhong S; Feng Q; Ning Z; Zhang Y
Med Phys; 2021 Aug; 48(8):4262-4278. PubMed ID: 34053092
[TBL] [Abstract][Full Text] [Related]
6. Global guidance network for breast lesion segmentation in ultrasound images.
Xue C; Zhu L; Fu H; Hu X; Li X; Zhang H; Heng PA
Med Image Anal; 2021 May; 70():101989. PubMed ID: 33640719
[TBL] [Abstract][Full Text] [Related]
7. SMU-Net: Saliency-Guided Morphology-Aware U-Net for Breast Lesion Segmentation in Ultrasound Image.
Ning Z; Zhong S; Feng Q; Chen W; Zhang Y
IEEE Trans Med Imaging; 2022 Feb; 41(2):476-490. PubMed ID: 34582349
[TBL] [Abstract][Full Text] [Related]
8. A novel segmentation method for breast ultrasound images based on neutrosophic l-means clustering.
Shan J; Cheng HD; Wang Y
Med Phys; 2012 Sep; 39(9):5669-82. PubMed ID: 22957633
[TBL] [Abstract][Full Text] [Related]
9. Breast ultrasound image segmentation: a survey.
Huang Q; Luo Y; Zhang Q
Int J Comput Assist Radiol Surg; 2017 Mar; 12(3):493-507. PubMed ID: 28070777
[TBL] [Abstract][Full Text] [Related]
10. A Discriminative Level Set Method with Deep Supervision for Breast Tumor Segmentation.
Hussain S; Xi X; Ullah I; Inam SA; Naz F; Shaheed K; Ali SA; Tian C
Comput Biol Med; 2022 Oct; 149():105995. PubMed ID: 36055157
[TBL] [Abstract][Full Text] [Related]
11. Multiscale superpixel method for segmentation of breast ultrasound.
Ilesanmi AE; Idowu OP; Makhanov SS
Comput Biol Med; 2020 Oct; 125():103879. PubMed ID: 32890977
[TBL] [Abstract][Full Text] [Related]
12. Ultrasonic breast tumor extraction based on adversarial mechanism and active contour.
Wang J; Chen G; Chen S; Joseph Raj AN; Zhuang Z; Xie L; Ma S
Comput Methods Programs Biomed; 2022 Oct; 225():107052. PubMed ID: 35985149
[TBL] [Abstract][Full Text] [Related]
13. Channel Attention Module With Multiscale Grid Average Pooling for Breast Cancer Segmentation in an Ultrasound Image.
Lee H; Park J; Hwang JY
IEEE Trans Ultrason Ferroelectr Freq Control; 2020 Jul; 67(7):1344-1353. PubMed ID: 32054578
[TBL] [Abstract][Full Text] [Related]
14. Segmentation of malignant lesions in 3D breast ultrasound using a depth-dependent model.
Tan T; Gubern-Mérida A; Borelli C; Manniesing R; van Zelst J; Wang L; Zhang W; Platel B; Mann RM; Karssemeijer N
Med Phys; 2016 Jul; 43(7):4074. PubMed ID: 27370126
[TBL] [Abstract][Full Text] [Related]
15. Deep weakly-supervised breast tumor segmentation in ultrasound images with explicit anatomical constraints.
Li Y; Liu Y; Huang L; Wang Z; Luo J
Med Image Anal; 2022 Feb; 76():102315. PubMed ID: 34902792
[TBL] [Abstract][Full Text] [Related]
16. Tumor segmentation in automated whole breast ultrasound using bidirectional LSTM neural network and attention mechanism.
Pan P; Chen H; Li Y; Cai N; Cheng L; Wang S
Ultrasonics; 2021 Feb; 110():106271. PubMed ID: 33166786
[TBL] [Abstract][Full Text] [Related]
17. BUS-Net: Breast Tumour Detection Network for Ultrasound Images Using Bi-directional ConvLSTM and Dense Residual Connections.
Arora R; Raman B
J Digit Imaging; 2023 Apr; 36(2):627-646. PubMed ID: 36515746
[TBL] [Abstract][Full Text] [Related]
18. SHA-MTL: soft and hard attention multi-task learning for automated breast cancer ultrasound image segmentation and classification.
Zhang G; Zhao K; Hong Y; Qiu X; Zhang K; Wei B
Int J Comput Assist Radiol Surg; 2021 Oct; 16(10):1719-1725. PubMed ID: 34254225
[TBL] [Abstract][Full Text] [Related]
19. BIRADS features-oriented semi-supervised deep learning for breast ultrasound computer-aided diagnosis.
Zhang E; Seiler S; Chen M; Lu W; Gu X
Phys Med Biol; 2020 Jun; 65(12):125005. PubMed ID: 32155605
[TBL] [Abstract][Full Text] [Related]
20. Spectral embedding based active contour (SEAC) for lesion segmentation on breast dynamic contrast enhanced magnetic resonance imaging.
Agner SC; Xu J; Madabhushi A
Med Phys; 2013 Mar; 40(3):032305. PubMed ID: 23464337
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
