Lymph node detection in CT scans using modified U-Net with residual learning and 3D deep network

[1] Terán MD(2014)Staging lymph node metastases from lung cancer in the mediastinum J Thorac Dis 6 230-137

[2] Brock MV(2016)Recist 1.1-update and clarification: from the recist committee Eur J Cancer 62 132-310

[3] Schwartz LH(2020)Lymph node detection method based on multisource transfer learning and convolutional neural network Int J Imag Syst Technol 30 298-986

[4] Litière S(2019)Semantic segmentation and detection of mediastinal lymph nodes and anatomical structures in ct data for lung cancer staging Int J Comput Assist Radiol Surg 14 977-637

[5] De Vries E(2022)Non-invasive precise staging of liver fibrosis using deep residual network model based on plain ct images Int J Comput Assist Radio Surg 17 627-114

[6] Ford R(2020)Resunet-a: a deep learning framework for semantic segmentation of remotely sensed data ISPRS J Photogramm Remote Sens 162 94-753

[7] Gwyther S(2018)Road extraction by deep residual U-Net IEEE Geosci Remote Sens Lett 15 749-1260

[8] Mandrekar S(2001)A statistical 3-d pattern processing method for computer-aided detection of polyps in ct colonography IEEE Trans Med Imaging 20 1251-250

[9] Shankar L(2011)Automatic detection and segmentation of lymph nodes from ct data IEEE Trans Med Imaging 31 240-undefined

[10] Bogaerts J(undefined)undefined undefined undefined undefined-undefined

[1] Terán MD(2014)Staging lymph node metastases from lung cancer in the mediastinum J Thorac Dis 6 230-137

[2] Brock MV(2016)Recist 1.1-update and clarification: from the recist committee Eur J Cancer 62 132-310

[3] Schwartz LH(2020)Lymph node detection method based on multisource transfer learning and convolutional neural network Int J Imag Syst Technol 30 298-986

[4] Litière S(2019)Semantic segmentation and detection of mediastinal lymph nodes and anatomical structures in ct data for lung cancer staging Int J Comput Assist Radiol Surg 14 977-637

[5] De Vries E(2022)Non-invasive precise staging of liver fibrosis using deep residual network model based on plain ct images Int J Comput Assist Radio Surg 17 627-114

[6] Ford R(2020)Resunet-a: a deep learning framework for semantic segmentation of remotely sensed data ISPRS J Photogramm Remote Sens 162 94-753

[7] Gwyther S(2018)Road extraction by deep residual U-Net IEEE Geosci Remote Sens Lett 15 749-1260

[8] Mandrekar S(2001)A statistical 3-d pattern processing method for computer-aided detection of polyps in ct colonography IEEE Trans Med Imaging 20 1251-250

[9] Shankar L(2011)Automatic detection and segmentation of lymph nodes from ct data IEEE Trans Med Imaging 31 240-undefined

[10] Bogaerts J(undefined)undefined undefined undefined undefined-undefined