122 related articles for article (PubMed ID: 38189528)
21. An active contour model for medical image segmentation with application to brain CT image.
Qian X; Wang J; Guo S; Li Q
Med Phys; 2013 Feb; 40(2):021911. PubMed ID: 23387759
[TBL] [Abstract][Full Text] [Related]
22. Design of lung nodules segmentation and recognition algorithm based on deep learning.
Yu H; Li J; Zhang L; Cao Y; Yu X; Sun J
BMC Bioinformatics; 2021 Nov; 22(Suppl 5):314. PubMed ID: 34749636
[TBL] [Abstract][Full Text] [Related]
23. A Segmentation Framework of Pulmonary Nodules in Lung CT Images.
Mukhopadhyay S
J Digit Imaging; 2016 Feb; 29(1):86-103. PubMed ID: 26055544
[TBL] [Abstract][Full Text] [Related]
24. 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]
25. Accurate segmentation for different types of lung nodules on CT images using improved U-Net convolutional network.
Zhang X; Liu X; Zhang B; Dong J; Zhang B; Zhao S; Li S
Medicine (Baltimore); 2021 Oct; 100(40):e27491. PubMed ID: 34622882
[TBL] [Abstract][Full Text] [Related]
26. Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks.
Tong N; Gou S; Yang S; Ruan D; Sheng K
Med Phys; 2018 Oct; 45(10):4558-4567. PubMed ID: 30136285
[TBL] [Abstract][Full Text] [Related]
27. Segmentation of pulmonary nodules in CT images based on 3D-UNET combined with three-dimensional conditional random field optimization.
Wu W; Gao L; Duan H; Huang G; Ye X; Nie S
Med Phys; 2020 Sep; 47(9):4054-4063. PubMed ID: 32428969
[TBL] [Abstract][Full Text] [Related]
28. 3D multi-view squeeze-and-excitation convolutional neural network for lung nodule classification.
Yang Y; Li X; Fu J; Han Z; Gao B
Med Phys; 2023 Mar; 50(3):1905-1916. PubMed ID: 36639958
[TBL] [Abstract][Full Text] [Related]
29. Deep Deconvolutional Residual Network Based Automatic Lung Nodule Segmentation.
Singadkar G; Mahajan A; Thakur M; Talbar S
J Digit Imaging; 2020 Jun; 33(3):678-684. PubMed ID: 32026218
[TBL] [Abstract][Full Text] [Related]
30. Fuzzy speed function based active contour model for segmentation of pulmonary nodules.
Chen K; Li B; Tian LF; Zhu WB; Bao YH
Biomed Mater Eng; 2014; 24(1):539-47. PubMed ID: 24211937
[TBL] [Abstract][Full Text] [Related]
31. Fast interactive medical image segmentation with weakly supervised deep learning method.
Girum KB; Créhange G; Hussain R; Lalande A
Int J Comput Assist Radiol Surg; 2020 Sep; 15(9):1437-1444. PubMed ID: 32653985
[TBL] [Abstract][Full Text] [Related]
32. Augmenting atlas-based liver segmentation for radiotherapy treatment planning by incorporating image features proximal to the atlas contours.
Li D; Liu L; Chen J; Li H; Yin Y; Ibragimov B; Xing L
Phys Med Biol; 2017 Jan; 62(1):272-288. PubMed ID: 27991439
[TBL] [Abstract][Full Text] [Related]
33. A few-shot U-Net deep learning model for lung cancer lesion segmentation via PET/CT imaging.
Protonotarios NE; Katsamenis I; Sykiotis S; Dikaios N; Kastis GA; Chatziioannou SN; Metaxas M; Doulamis N; Doulamis A
Biomed Phys Eng Express; 2022 Feb; 8(2):. PubMed ID: 35144242
[TBL] [Abstract][Full Text] [Related]
34. Superpixel-based deep convolutional neural networks and active contour model for automatic prostate segmentation on 3D MRI scans.
da Silva GLF; Diniz PS; Ferreira JL; França JVF; Silva AC; de Paiva AC; de Cavalcanti EAA
Med Biol Eng Comput; 2020 Sep; 58(9):1947-1964. PubMed ID: 32566988
[TBL] [Abstract][Full Text] [Related]
35. An integrated segmentation and shape-based classification scheme for distinguishing adenocarcinomas from granulomas on lung CT.
Alilou M; Beig N; Orooji M; Rajiah P; Velcheti V; Rakshit S; Reddy N; Yang M; Jacono F; Gilkeson RC; Linden P; Madabhushi A
Med Phys; 2017 Jul; 44(7):3556-3569. PubMed ID: 28295386
[TBL] [Abstract][Full Text] [Related]
36. Segmentation of pulmonary nodules using adaptive local region energy with probability density function-based similarity distance and multi-features clustering.
Li B; Chen Q; Peng G; Guo Y; Chen K; Tian L; Ou S; Wang L
Biomed Eng Online; 2016 May; 15(1):49. PubMed ID: 27150553
[TBL] [Abstract][Full Text] [Related]
37. Liver segmentation in abdominal CT images via auto-context neural network and self-supervised contour attention.
Chung M; Lee J; Park S; Lee CE; Lee J; Shin YG
Artif Intell Med; 2021 Mar; 113():102023. PubMed ID: 33685586
[TBL] [Abstract][Full Text] [Related]
38. CoLe-CNN: Context-learning convolutional neural network with adaptive loss function for lung nodule segmentation.
Pezzano G; Ribas Ripoll V; Radeva P
Comput Methods Programs Biomed; 2021 Jan; 198():105792. PubMed ID: 33130496
[TBL] [Abstract][Full Text] [Related]
39. The effects of physics-based data augmentation on the generalizability of deep neural networks: Demonstration on nodule false-positive reduction.
Omigbodun AO; Noo F; McNitt-Gray M; Hsu W; Hsieh SS
Med Phys; 2019 Oct; 46(10):4563-4574. PubMed ID: 31396974
[TBL] [Abstract][Full Text] [Related]
40. AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy.
Zhu W; Huang Y; Zeng L; Chen X; Liu Y; Qian Z; Du N; Fan W; Xie X
Med Phys; 2019 Feb; 46(2):576-589. PubMed ID: 30480818
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]