3D Kidneys and Kidney Tumor Semantic Segmentation using Boundary-Aware Networks

09/14/2019
by   Andriy Myronenko, et al.
33

Automated segmentation of kidneys and kidney tumors is an important step in quantifying the tumor's morphometrical details to monitor the progression of the disease and accurately compare decisions regarding the kidney tumor treatment. Manual delineation techniques are often tedious, error-prone and require expert knowledge for creating unambiguous representation of kidneys and kidney tumors segmentation. In this work, we propose an end-to-end boundary aware fully Convolutional Neural Networks (CNNs) for reliable kidney and kidney tumor semantic segmentation from arterial phase abdominal 3D CT scans. We propose a segmentation network consisting of an encoder-decoder architecture that specifically accounts for organ and tumor edge information by devising a dedicated boundary branch supervised by edge-aware loss terms. We have evaluated our model on 2019 MICCAI KiTS Kidney Tumor Segmentation Challenge dataset and our method has achieved dice scores of 0.9742 and 0.8103 for kidney and tumor repetitively and an overall composite dice score of 0.8923.

READ FULL TEXT

page 2

page 3

page 7

research
08/21/2019

Boundary Aware Networks for Medical Image Segmentation

Fully convolutional neural networks (CNNs) have proven to be effective a...
research
11/01/2021

Redundancy Reduction in Semantic Segmentation of 3D Brain Tumor MRIs

Another year of the multimodal brain tumor segmentation challenge (BraTS...
research
01/06/2020

Robust Semantic Segmentation of Brain Tumor Regions from 3D MRIs

Multimodal brain tumor segmentation challenge (BraTS) brings together re...
research
01/25/2018

Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans

This paper reports Deep LOGISMOS approach to 3D tumor segmentation by in...
research
11/15/2022

Encoding feature supervised UNet++: Redesigning Supervision for liver and tumor segmentation

Liver tumor segmentation in CT images is a critical step in the diagnosi...
research
05/17/2022

blob loss: instance imbalance aware loss functions for semantic segmentation

Deep convolutional neural networks have proven to be remarkably effectiv...
research
03/09/2021

Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining

The boundary of tumors (hepatocellular carcinoma, or HCC) contains rich ...

Please sign up or login with your details

Forgot password? Click here to reset