Comments (4)
Processing from original size into 28 will absolutely lead to lost details. However, it’s not our emphasis.
For 3D images, the original size is generally not that large because we use the VOIs. In terms of how, please refer to our paper.
Jiancheng
from medmnist.
Thank you for your response.
I didn't find a specific description of the processing method for 3D data in the paper. Regarding the dimensions of the sequence axis, if it cannot reach 28 or exceeds 28, there are several possible ways to handle it. For example, if you have a lung nodule and the sequence length in the depth size is 10, one approach is to resize or crop the volume to a size of 28 by using a bounding box that captures the region of interest. Alternatively, interpolation or zero-padding can be used. Regarding this point, could you explain it in detai, thanks a lot.
from medmnist.
In fact we’ve described it: “ …center-crop the spatially normalized images (with a spacing of 1 mm × 1 mm × 1 mm) into 28 × 28 × 28.”
there is no magic; what we do is cropping and resizing. If you would like to investigate the impact of resizing, I suggest to use the original version.
from medmnist.
thanks again
from medmnist.
Related Issues (20)
- [feature request] the 3d dataset convert from npz to dicom HOT 5
- running getting_started_without_PyTorch notebook report error HOT 1
- License problem and use of this dataset? HOT 3
- Larger image options- 64*64 or 128*128? HOT 4
- Generation of OrganMNIST {Axial,Coronal,Sagittal} HOT 2
- How to understand the label array HOT 1
- all images download as .npz
- Encountering `BadZipFile` Bug When Loading `pathmnist.npz` Locally HOT 2
- Request for preprocessing code HOT 2
- How to use the latest 64, 128 and 224 version of dataset with data_flag without downloading externally? HOT 2
- download by Command Line Tools | Something went wrong when downloading HOT 4
- Benchmark about Medmnist+ HOT 1
- How to visualise data without montage? HOT 2
- Easy way to combine datasets? HOT 2
- Question about chestmnist dataset HOT 2
- Citation to PneumoniaMNIST original source HOT 1
- Labelling vs ground truth HOT 2
- Where can I find sample IDs? HOT 2
- Custom Dataset Usage 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 medmnist.