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Segmentation of prostate from MRI scans

License: GNU General Public License v3.0

Python 100.00%
deep-learning fully-convolutional-networks medical-imaging mri-images python tensorflow

3d-prostate-segmentation's Introduction

I am Aman Agarwal 👨‍💻

  • R&D Engineer at Synopsys Inc.
  • Skilled in deep learning 🤖, android, and cloud.
  • If not a programmer 💻, I would be a body builder 💪.
  • Certified AWS ML specialist, solutions architect, and developer ☁️✔️.
  • Certified TensorFlow developer.

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3d-prostate-segmentation's Issues

node IteratorGetNext error

Hi,
I tried to launch the training, but I got this error:

InvalidArgumentError (see above for traceback): Cannot batch tensors with different shapes in component 0. First element had shape [512,512,29] and element 1 had shape [512,512,54].

 [[node IteratorGetNext (defined at D:/1_Deep_learning/codes/Segmentation_Deep_learing/3d-prostate-segmentation-master/train.py:53) ]]
 [[node IteratorGetNext (defined at D:/1_Deep_learning/codes/Segmentation_Deep_learing/3d-prostate-segmentation-master/train.py:53) ]]

Is it because you are using a different version of tensorflow from mine?
I have the 1.13.1 tensorflow gpu

Thanks in advance

division by zero

hi
I had the following error "" sum(train_loss)/len(train_loss), sum(val_loss)/len(val_loss), time.time()-start_time))
"" even i put 40 samples for train-data and 10 samples for val-data, I think that len(train_loss) and len(val_loss) have zero value.
Please let me know if you have any idea.

Output from predict.py

I would like to make prediction based on my trained model. I put my test data in the folder of val-data and run predict.py. The code is running, however, I don't see any output of segmentation image after the code has been executed successfully. I would like to know what the output I should see on predict.py?

Thanks.

some confusion about metric_eval.py: hd(Hausdorff Distance)、asd(Average surface distance metric)、assd( Average symmetric surface distance)

Hi,@amanbasu

Thank you for sharing such a great repo.I use metrics in the metric_eval.py to evaluate my own segmentation results.But I have some confusion about hd(Hausdorff Distance)、asd(Average surface distance metric)、assd( Average symmetric surface distance), could you give me some help ?

Q1:How do I determine the value of voxelspacing and the value of connectivity? I should use the default value(voxelapacing=None,connectivity=1) ,
Or the connectivity value needs to be greater than 1?And voxelapacing=(z_spacing,y_spacing,x_spacing )(the voxelspacing of my dataset is specified:(x,y,z)=(0.7031, 0.7031, 4))?
####################################################################################
In the comments section below:
connectivity : int
The neighbourhood/connectivity considered when determining the surface
of the binary objects. This value is passed to scipy.ndimage.morphology.generate_binary_structure and should usually be :math:> 1. Note that the connectivity influences the result in the case of the Hausdorff distance.
#####################################################################################
I set the value of connectivity to 1 and 2, I get different hd value ..Could you give me some advice?

Q2: In your article, Could you tell me what Avg. Boundary Distance in Tabels 3 refer to in the metric_eval.py?I can't find this part of the code.Could you give me some help?

Q3:I read the comments on asd and obj_asd carefully, but I still don't understand what the difference is.Could you give me some guidance?

Q4:when i use asd() in the metric_eval.py,the results I got were a little strange.for example:testsets:40 case,I used metrics in the metric_eval.py to get dice =0.923±0.019,hd95=2.078±1.379,asd=0.545±0.138,I feel that asd value is a bit strange,it is too small, each case has a value less than 1.I don't know if asd value that i calculated is correct, could you give me some guidance?
image

Thanks in advance.
Looking forward your reply.
Best.

Respacing

Hi, thanks for sharing your great work. I am trying to follow your implementation on my own task. According to your poster, the images are resized and respaced. However, according to the github code, I think you only re-size the MRI images. Am I wrong ? Do I need to further re-space the MRI images ?

How to reproduce results

Please guide how to reproduce results step by step, such as :
where to place dataset, the order of file running and so on.
tnx for your help

Example

Hi,
thank you for sharing such great work, I am trying to apply your work I faced some issues could you please provide us with simple example or procedure to follow the work and what is expected to see after each step.

Thank you

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