Comments (1)
Thanks for your interests. Actually, in this paper, We only use the dice loss, named as Loss_seg_dice, for the model training. Here, the CE loss is just computed but not introduced for the training. You can check the paper for the details. Thanks.
from mc-net.
Related Issues (16)
- Did you crop raw samples on the z axis? HOT 1
- 请问可以提供预处理好的Pancreas数据吗? HOT 1
- Asking for the CT-82 dataset HOT 1
- Pancreas dataset preprocessing success,but the DICE score fluctuated around 0.2 to 0.1 during training. HOT 4
- 关于Multi-scale MC-Net+和sharpening函数问题请教 HOT 1
- About the parameter quantity in the MC-Net+ HOT 2
- Number of classes issue HOT 1
- Labels for unlabeled data HOT 3
- 训练标签问题 HOT 1
- train_mcnet_2d.py HOT 3
- About the consistency_weight HOT 1
- Data preparation for ACDC, LA and Pancreas HOT 6
- Type error when training VNet with 10% LA dataset HOT 3
- Unmatched tensors HOT 12
- Train VNet with all 80 labels HOT 1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from mc-net.