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Dice loss function #10

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wyli opened this issue Jan 10, 2020 · 1 comment · Fixed by #27
Closed

Dice loss function #10

wyli opened this issue Jan 10, 2020 · 1 comment · Fixed by #27
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@fepegar @ericspod @Nic-Ma

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@wyli
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wyli commented Jan 10, 2020

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@fepegar
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fepegar commented Jan 10, 2020

I have an implementation here: https://weisslab.cs.ucl.ac.uk/FernandoPerezGarcia/episurg/blob/master/episurg/loss.py

@wyli wyli assigned fepegar and Nic-Ma and unassigned yanchengnv Jan 10, 2020
@wyli wyli mentioned this issue Jan 14, 2020
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@wyli wyli closed this as completed in #27 Jan 17, 2020
Nic-Ma added a commit that referenced this issue Jun 26, 2020
@wyli @wentaozhu
@ntenenz @Nic-Ma
model parallel training research (#616)
379c959 
* adds network

* adds basic training

* update loading

* working prototype

* update validation set

* [MONAI] Add author; paper info; PDDCA18 (#6)

+ Author
+ Early accept
+ PDDCA18 link

* Update README.md

* adds network

* adds basic training

* update loading

* working prototype

* update validation set

* [MONAI] Update TRAIN_PATH, VAL_PATH (#8)

+ Update TRAIN_PATH, VAL_PATH

* [MONAI] Add data link (#7)

+ Add data link https://drive.google.com/file/d/1A2zpVlR3CkvtkJPvtAF3-MH0nr1WZ2Mn/view?usp=sharing

* fixes typos

* tested new dataset

* print more infor, checked new dataset

* [MONAI] Add paper link (#9)

Add paper link https://arxiv.org/abs/2006.12575

* [MONAI] Use dice loss + focal loss to train (#10)

Use dice loss + focal loss to train

* [MONAI] Support non-one-hot ground truth (#11)

Support non-one-hot ground truth

* fixes format and docstrings, adds argparser options

* resume the focal_loss

* adds tests

* [MONAI] Support non-one-hot ground truth (#11)

Support non-one-hot ground truth

* adds tests

* update docstring

* [MONAI] Keep track of best validation scores (#12)

Keep track of best validation scores

* model saving

* adds window sampling

* update readme

* update docs

* fixes flake8 error

* update window sampling

* fixes model name

* fixes channel size issue

* [MONAI] Update --pretrain, --lr (#13)

+ lr from 5e-4 to 1e-3 because we use mean for class channel instead of sum for class channel.
+ pretrain path is consistent with current model_name.

* [MONAI] Pad image; elastic; best class model (#14)

* [MONAI] Pad image; elastic; best class model

+ Pad image bigger than crop_size, avoid potential issues in RandCropByPosNegLabeld
+ Use Rand3DElasticd
+ Save best model for each class

* Update train.py

Co-authored-by: Wenqi Li <wenqil@nvidia.com>

* flake8 fixes

* removes -1 cropsize deform

* testing commands

* fixes unit tests

* update spatial padding

* [MONAI] Add full image deform augmentation (#15)

+ Add full image deform augmentation by Rand3DElasticd
+ Please use latest MONAI in #623

* Adding py.typed

* updating setup.py to comply with black

* update based on comments

* excluding research from packaging

* update tests

* update setup.py

Co-authored-by: Wentao Zhu <wentaozhu1991@gmail.com>
Co-authored-by: Neil Tenenholtz <ntenenz@users.noreply.github.com>
Co-authored-by: Nic Ma <nma@nvidia.com>
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@fepegar fepegar

@ericspod ericspod

@Nic-Ma Nic-Ma

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initial unit tests for dice loss Project-MONAI/MONAI
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@wyli @fepegar @ericspod @Nic-Ma @yanchengnv