Medical Image Segmentation Algorithm Based on Bilateral Fusion

Liming Liang; Jiang Yin; Yuanyuan Wu; Jun Feng

doi:10.3788/LOP202259.0817003

[1] Lê M, Unkelbach J, Ayache N et al. GPSSI: Gaussian process for sampling segmentations of images[M]. Navab N, Hornegger J, Wells W M, et al. Medical image computing and computer-assisted intervention-MICCAI 2015. Lecture notes in computer science, 9351, 38-46(2015).

[2] Song J, Xiao L, Lian Z C et al. Overview and prospect of deep learning for image segmentation in digital pathology[J]. Journal of Software, 32, 1427-1460(2021).

[3] Long J, Shelhamer E, Darrell T. Fully convolutional networks for semantic segmentation[C], 3431-3440(2015).

[4] Ronneberger O, Fischer P, Brox T. U-Net: convolutional networks for biomedical image segmentation[M]. Navab N, Hornegger J, Wells W M, et al. Medical image computing and computer-assisted intervention-MICCAI 2015. Lecture notes in computer science, 9351, 234-241(2015).

[5] Zhang Z X, Liu Q J, Wang Y H. Road extraction by deep residual U-Net[J]. IEEE Geoscience and Remote Sensing Letters, 15, 749-753(2018).

[6] Ibtehaz N, Rahman M S. MultiResUNet: rethinking the U-Net architecture for multimodal biomedical image segmentation[J]. Neural Networks, 121, 74-87(2020).

[7] Oktay O, Schlemper J, Folgoc L L et al. Attention U-Net: learning where to look for the pancreas[EB/OL]. https://arxiv.org/abs/1804.03999

[8] Tian F Y, Zhou M Q, Yan F et al. Spinal CT segmentation based on AttentionNet and DenseUnet[J]. Laser & Optoelectronics Progress, 57, 201008(2020).

[9] Sekuboyina A, Kukačka J, Kirschke J S et al. Attention-driven deep learning for pathological spine segmentation[M]. Glocker B, Yao J H, Vrtovec T, et al. Computational methods and clinical applications in musculoskeletal imaging. Lecture notes in computer science, 10734, 108-119(2018).

[10] Jha D, Smedsrud P H, Riegler M A et al. ResUNet++: an advanced architecture for medical image segmentation[C], 225-230(2019).

[11] Zhou Z W, Siddiquee M M R, Tajbakhsh N et al. UNet++: redesigning skip connections to exploit multiscale features in image segmentation[J]. IEEE Transactions on Medical Imaging, 39, 1856-1867(2020).

[12] Wang J D, Sun K, Cheng T et al. Deep high-resolution representation learning for visual recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43, 3349-3364(2021).

[13] Jha D, Smedsrud P H, Riegler M A et al. Kvasir-SEG: a segmented polyp dataset[M]. Ro Y M, Cheng W H, Kim J, et al. MultiMedia modeling. Lecture notes in computer science, 11962, 451-462(2019).

[14] Gutman D, Codella N C F, Celebi M E et al. Skin lesion analysis toward melanoma detection: a challenge at the international symposium on biomedical imaging (ISBI)2016, hosted by the international skin imaging collaboration (ISIC)[EB/OL]. https://arxiv.org/abs/1605.01397

[15] Codella N C F, Gutman D, Celebi M E et al. Skin lesion analysis toward melanoma detection: a challenge at the 2017 international symposium on biomedical imaging (ISBI), hosted by the international skin imaging collaboration (ISIC)[C], 168-172(2018).

[16] Liu S T, Huang D, Wang Y H. Receptive field block net for accurate and fast object detection[M]. Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science, 11215, 404-419(2018).

[17] Wu Z, Su L, Huang Q M. Cascaded partial decoder for fast and accurate salient object detection[C], 3902-3911(2019).

[18] Yun D, Ryu J, Lim J. Dual aggregated feature pyramid network for multi label classification[J]. Pattern Recognition Letters, 144, 75-81(2021).

[19] Yu C Q, Gao C X, Wang J B et al. BiSeNet V2: bilateral network with guided aggregation for real-time semantic segmentation[EB/OL]. https://arxiv.org/abs/2004.02147v1

[20] Huang C H, Wu H Y, Lin Y L et al. HarDNet-MSEG: a simple encoder-decoder polyp segmentation neural network that achieves over0.9 dicemean and 86 fps[EB/OL]. https://arxiv.org/abs/2101.07172

[21] Zhang H L, Li Q, Guan X. An improved three-dimensional dual-path brain tumor image segmentation network[J]. Acta Optica Sinica, 41, 0310002(2021).

[22] Jha D, Ali S, Tomar N K et al. Real-time polyp detection, localization and segmentation in colonoscopy using deep learning[EB/OL]. https://arxiv.org/abs/2011.07631

[23] Jha D, Riegler M A, Johansen D et al. DoubleU-net: a deep convolutional neural network for medical image segmentation[C], 558-564(2020).

[24] Zhao H S, Shi J P, Qi X J et al. Pyramid scene parsing network[C], 6230-6239(2017).

[25] Chen L C, Zhu Y K, Papandreou G et al. Encoder-decoder with atrous separable convolution for semantic image segmentation[M]. Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science, 11211, 833-851(2018).

[26] Zhang Q, Cui Z P, Niu X G et al. Image segmentation with pyramid dilated convolution based on ResNet and U-Net[M]. Liu D R, Xie S L, Li Y Q, et al. Neural information processing. Lecture notes in computer science, 10635, 364-372(2017).

[27] Qin X B, Zhang Z C, Huang C Y et al. U2-Net: going deeper with nested U-structure for salient object detection[J]. Pattern Recognition, 106, 107404(2020).