Coarse to Fine Framework for Kidney Tumor Segmentation

2019 ◽  
Author(s):  
Shuolin Liu
Keyword(s):  
Tumor Segmentation ◽  
Kidney Tumor ◽  
Coarse To Fine

Submission to the Kidney Tumor Segmentation Challenge 2019

2019 ◽  
Author(s):  
Pengxin Yu ◽  
Xing Cui ◽  
Xi Tian ◽  
Jiechao Ma ◽  
Rongguo Zhang
Keyword(s):  
Tumor Segmentation ◽  
Kidney Tumor

scholarly journals Kidney Tumor Segmentation and Classification on Abdominal CT Scans

2017 ◽  
Vol 164 (9) ◽  
pp. 1-5 ◽  
Author(s):  
Bansari Shah ◽  
Charmi Sawla ◽  
Shraddha Bhanushali ◽  
Poonam Bhogale
Keyword(s):  
Ct Scans ◽  
Tumor Segmentation ◽  
Kidney Tumor ◽  
Abdominal Ct

scholarly journals Kidney and Kidney Tumor Segmentation using a Logical Ensemble of U-nets with Volumetric Validation

2019 ◽  
Author(s):  
Jamie A. O'Reilly ◽  
Manas Sangworasil ◽  
Takenobu Matsuura
Keyword(s):  
Tumor Segmentation ◽  
Kidney Tumor

scholarly journals Comparison of Unet3D Models for Kidney Tumor Segmentation

2020 ◽  
Author(s):  
Fuat Turk ◽  
Murat Luy ◽  
Necaattin Barisci
Keyword(s):  
Image Segmentation ◽  
Surgical Treatment ◽  
Kidney Cancer ◽  
Diagnostic Methods ◽  
Disease Spread ◽  
Tumor Segmentation ◽  
Kidney Tumor ◽  
Industrialized Countries ◽  
Kidney Tumors ◽  
Cancer Types

Worldwide, hundreds of thousands of people are diagnosed with kidney cancer and this disease is more common in developed and industrialized countries. Previously, kidney cancer was known as an elderly disease and was seen in people over a certain age; nowadays it is also seen in younger individuals and it is easier to diagnose thanks to new radiological diagnostic methods. A kidney tumor is a type of cancer that is extremely aggressive and needs surgical treatment rapidly. Today, approximately 30% of patients diagnosed with kidney cancer are unfortunately noticed at the stage of metastatic disease (spread to distant organs). The biggest factor that pushes us to this study is that kidney tumors progress unlike other cancer types with little or no symptoms. Therefore, conducting such studies is extremely important for early diagnosis. In this study, we compare the Unet3D models in order to help people who are dealing with difficulties in the diagnosis of kidney cancer. Unet, Unet+ResNet and Unet++ models were compared for image segmentation.

scholarly journals A Multi-scale Attention Network for Kidney Tumor Segmentation on CT Scans

2019 ◽  
Author(s):  
Liyan Sun ◽  
Weihong Zeng ◽  
Xinghao Ding ◽  
Yue Huang
Keyword(s):  
Ct Scans ◽  
Tumor Segmentation ◽  
Kidney Tumor ◽  
Attention Network ◽  
Multi Scale
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