MONAI
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Project-MONAI
AI Toolkit for Healthcare Imaging
**Is your feature request related to a problem? Please describe.** Richard's tutorial [video_seg](https://github.com/Project-MONAI/tutorials/blob/1d7d0863d43e7ce1641154f6e8b2db0f80e5d963/modules/video_seg.ipynb) has a great application value on deploying segmentation models on video streams. However, trivial works like splitting...
**Is your feature request related to a problem? Please describe.** when it's input is a metatensor, `monai.visualize.matshow3d` should have an option to display the image content with the actual aspect...
Fixes #4609 ### Description This PR added the AUCMLoss ### Status **Work in progress** ### Types of changes - [x] Non-breaking change (fix or new feature that would not break...
**Is your feature request related to a problem? Please describe.** The DatasetSummary class computes the dataset statistics (e.g. mean pixel intensity, ...) based on the image **and** its label. However,...
Hey folks! It would be cool to have details on the MONAI working groups included in the contributing guide since in many cases it seems like there are lots of...
### Discussed in https://github.com/Project-MONAI/MONAI/discussions/4807 Originally posted by **ChenglongWang** August 1, 2022 Recently, I noticed that the `pixdim` argument from the `Spacing` transform is inconsistent with other transforms. For the `pixdim`...
Similar to radiology where we have a common `MetaTensor` properties and have employed them in radiology transforms, we need to explore the best way to leverage `MetaTensor` for pathology components...
Stain normalization in MONAI consists of two components stain extraction and stain normalization. Right now, they are specific to Hematoxylin and Eosin stains but both of these components can be...
**Is your feature request related to a problem? Please describe.** Several segmentation pipelines, and in particular interactive segementation ones, rely on some form of distance transform (e.g. Euclidean, Chamfer or...
**Is your feature request related to a problem? Please describe.** In super-resolution networks, a low resolution input is upsampled using a neural networks often with an integer factor (e.g. x2,...
