From 326c0a573fd5f0dc40883a1b376f404cf5941390 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Thomas=20K=C3=BCnzel?= Date: Wed, 18 Dec 2024 16:18:01 +0100 Subject: [PATCH] updated fMRI denoiser model and moved fMRI example to other (as it is not in the same state as the ephys and ophys) --- +deepinterp/+internal/fmriDenoiserNetwork.m | 82 +++++++++++------- README.md | 2 +- examples/fMRI_OpenNeuro.mlx | Bin 381226 -> 0 bytes examples/other/fMRI_OpenNeuro.mlx | Bin 0 -> 567186 bytes gettingStarted.mlx | Bin 3595 -> 3542 bytes ...n_absolute_error_2020_08_28_00_25_model.h5 | Bin 0 -> 417328 bytes .../fmri_pretrained_matlab_compatible.mat | Bin 172015 -> 443915 bytes 7 files changed, 51 insertions(+), 33 deletions(-) delete mode 100644 examples/fMRI_OpenNeuro.mlx create mode 100644 examples/other/fMRI_OpenNeuro.mlx create mode 100644 pretrainedModels/2020_08_28_00_25_fmri_unet_denoiser_mean_absolute_error_2020_08_28_00_25_model.h5 diff --git a/+deepinterp/+internal/fmriDenoiserNetwork.m b/+deepinterp/+internal/fmriDenoiserNetwork.m index 07a4eb2..2b47ae7 100644 --- a/+deepinterp/+internal/fmriDenoiserNetwork.m +++ b/+deepinterp/+internal/fmriDenoiserNetwork.m @@ -1,65 +1,83 @@ -function net = fmriDenoiserNetwork(modelPath, pretrainedNetwork) -%fmriDenoiserNetwork - generate MATLAB Version of the DeepInterpolation fMRI-Denoiser +function net = fmriDenoiserNetwork(preN) +%FMRIDENOISERNETWORK - MATLAB Version of the DeepInterpolation fMRI-Denoiser -lgraph = layerGraph(); +resize = true; -tempLayers = [ - image3dInputLayer([7 7 7 5],"Name","image3dinput",'Normalization','none'); - convolution3dLayer([3 3 3],8,"Name","conv3d","Padding","same","Weights",mywini(1),"Bias",mybini(1)); - reluLayer("Name","relu1")]; -lgraph = addLayers(lgraph,tempLayers); +lgraph = layerGraph(); +poolsize = [2 2 2]; +poolargs={"Stride",poolsize}; +convargs={"Padding","same"}; +resizeLayers1 = [ + resize3dLayer("Scale",2,"Name","up1"); + functionLayer(@zeropad,"Name","pad1",Formattable=true,Acceleratable=true)]; +resizeLayers2 = [ + resize3dLayer("Scale",2,"Name","up2") + functionLayer(@zeropad,"Name","pad2",Formattable=true,Acceleratable=true)]; +cc1="pad1"; cc2="pad2"; -tempLayers = [ - maxPooling3dLayer([3 3 3],"Name","pool1","Padding","same") - convolution3dLayer([3 3 3],16,"Name","conv3d_1","Padding","same","Weights",mywini(2),"Bias",mybini(2)) - reluLayer("Name","relu2")]; -lgraph = addLayers(lgraph,tempLayers); +if ~resize + poolargs={"Padding","same"}; + resizeLayers1=[]; resizeLayers2=[]; + cc1="relu3"; cc2="relu4"; +end tempLayers = [ - maxPooling3dLayer([3 3 3],"Name","pool2","Padding","same") - convolution3dLayer([3 3 3],32,"Name","conv3d_2","Padding","same","Weights",mywini(3),"Bias",mybini(3)) - reluLayer("Name","relu3")]; + image3dInputLayer([7 7 7 5],"Name","image3dinput","Normalization","none") + convolution3dLayer([3 3 3],8,"Name","conv1",convargs{:},"Weights",mywini(1,preN),"Bias",mybini(1,preN)) + reluLayer("Name","relu1") + maxPooling3dLayer(poolsize,"Name","pool1",poolargs{:}) + convolution3dLayer([3 3 3],16,"Name","conv2",convargs{:},"Weights",mywini(2,preN),"Bias",mybini(2,preN)) + reluLayer("Name","relu2") + maxPooling3dLayer(poolsize,"Name","pool2",poolargs{:}) + convolution3dLayer([3 3 3],32,"Name","conv3",convargs{:},"Weights",mywini(3,preN),"Bias",mybini(3,preN)) + reluLayer("Name","relu3") + resizeLayers1]; lgraph = addLayers(lgraph,tempLayers); tempLayers = [ depthConcatenationLayer(2,"Name","conc_up_1") - convolution3dLayer([3 3 3],16,"Name","conv3d_3","Padding","same","Weights",mywini(4),"Bias",mybini(4)) - reluLayer("Name","relu4")]; + convolution3dLayer([3 3 3],16,"Name","conv4",convargs{:},"Weights",mywini(4,preN),"Bias",mybini(4,preN)) + reluLayer("Name","relu4") + resizeLayers2]; lgraph = addLayers(lgraph,tempLayers); +lgraph = connectLayers(lgraph,cc1,"conc_up_1/in1"); +lgraph = connectLayers(lgraph,"relu2","conc_up_1/in2"); tempLayers = [ depthConcatenationLayer(2,"Name","conc_up_2") - convolution3dLayer([3 3 3],8,"Name","conv3d_4","Padding","same","Weights",mywini(5),"Bias",mybini(5)) + convolution3dLayer([3 3 3],8,"Name","conv5",convargs{:},"Weights",mywini(5,preN),"Bias",mybini(5,preN)) reluLayer("Name","relu5") - convolution3dLayer([1 1 1],1,"Name","conv3d_5","Padding","same","Weights",mywini(6),"Bias",mybini(6)) + convolution3dLayer([1 1 1],1,"Name","out",convargs{:},"Weights",mywini(6,preN),"Bias",mybini(6,preN)) regressionLayer("Name","out_r")]; lgraph = addLayers(lgraph,tempLayers); +lgraph = connectLayers(lgraph,cc2,"conc_up_2/in1"); +lgraph = connectLayers(lgraph,"relu1","conc_up_2/in2"); clear tempLayers; -lgraph = connectLayers(lgraph,"relu1","pool1"); -lgraph = connectLayers(lgraph,"relu1","conc_up_2/in2"); -lgraph = connectLayers(lgraph,"relu2","pool2"); -lgraph = connectLayers(lgraph,"relu2","conc_up_1/in2"); -lgraph = connectLayers(lgraph,"relu3","conc_up_1/in1"); -lgraph = connectLayers(lgraph,"relu4","conc_up_2/in1"); - net = assembleNetwork(lgraph); -save(modelPath,"net") +end + + +%% Local Functions -function w = mywini(ilayer) +function w = mywini(ilayer, preN) lwlnames = {'conv3d','conv3d_1','conv3d_2','conv3d_3','conv3d_4','conv3d_5'}; %layers_with_learnables lname = lwlnames{ilayer}; -thisweights = h5read(pretrainedNetwork,strcat('/model_weights/',lname,'/',lname,'/kernel:0')); +thisweights = h5read(preN,strcat('/model_weights/',lname,'/',lname,'/kernel:0')); w = permute(thisweights,[5,4,3,2,1]); end -function b = mybini(ilayer) +function b = mybini(ilayer, preN) lwlnames = {'conv3d','conv3d_1','conv3d_2','conv3d_3','conv3d_4','conv3d_5'}; %layers_with_learnables lwldims = [8 16 32 16 8 1]; lname = lwlnames{ilayer}; -b = h5read(pretrainedNetwork,strcat('/model_weights/',lname,'/',lname,'/bias:0')); +b = h5read(preN,strcat('/model_weights/',lname,'/',lname,'/bias:0')); b = reshape(b,[1 1 1 lwldims(ilayer)]); end +function out = zeropad(in) +m = extractdata(in); +n = padarray(m,[1 1 1],0,"post"); +out = dlarray(n); end \ No newline at end of file diff --git a/README.md b/README.md index 4b0c0be..78668c9 100644 --- a/README.md +++ b/README.md @@ -42,7 +42,7 @@ Expected use cases will involve larger data sizes, for which remote data locatio | Data Type | Pretrained Model | Public Data Archive | View :eyes: | Run ▶️ |---|---|---|---|---| |🔬"Ophys" (optical physiology) | [model](pretrainedModels/pretrained.json) | [Allen Brain Observatory](http://allen-brain-observatory.s3.amazonaws.com/visual-coding-2p/ophys_movies/ophys_experiment_496908818.h5) (55.6 GB) | [![View Deep-Interpolation-MATLAB on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://viewer.mathworks.com/?viewer=live_code&url=https%3A%2F%2Fwww.mathworks.com%2Fmatlabcentral%2Fmlc-downloads%2Fdownloads%2F84c22101-bffc-435a-910c-b0c7dcd5b386%2F29e7e92d-4639-4178-8e19-739580981e60%2Ffiles%2Fexamples%2Fophys_AllenBrainObservatory.mlx&embed=web) | (\*) | -|🧠 fMRI (functional magnetic resonance imaging) | [TODO](pretrainedModels/pretrained.json) (AWS)| [Open Neuro](https://openneuro.org/datasets/ds001246/versions/1.2.1) (18.3 GB)| [![View Deep-Interpolation-MATLAB on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://viewer.mathworks.com/?viewer=live_code&url=https%3A%2F%2Fwww.mathworks.com%2Fmatlabcentral%2Fmlc-downloads%2Fdownloads%2F84c22101-bffc-435a-910c-b0c7dcd5b386%2F29e7e92d-4639-4178-8e19-739580981e60%2Ffiles%2Fexamples%2Ftiny_fMRI_inference.mlx&embed=web) | [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=INCF/DeepInterpolation-MATLAB&file=examples/fMRI_OpenNeuro.mlx) +|🧠 fMRI (functional magnetic resonance imaging) | [TODO](pretrainedModels/pretrained.json) (AWS)| [Open Neuro](https://openneuro.org/datasets/ds001246/versions/1.2.1) (18.3 GB)| [![View Deep-Interpolation-MATLAB on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://viewer.mathworks.com/?viewer=live_code&url=https%3A%2F%2Fwww.mathworks.com%2Fmatlabcentral%2Fmlc-downloads%2Fdownloads%2F84c22101-bffc-435a-910c-b0c7dcd5b386%2F29e7e92d-4639-4178-8e19-739580981e60%2Ffiles%2Fexamples%2Ftiny_fMRI_inference.mlx&embed=web) | [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=INCF/DeepInterpolation-MATLAB&file=examples/other/fMRI_OpenNeuro.mlx) (\*) 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