junqiangchen / luna16-lung-nodule-analysis-2016-challenge Goto Github PK
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Home Page: https://luna16.grand-challenge.org/
LUNA16-Lung-Nodule-Analysis-2016-Challenge
Home Page: https://luna16.grand-challenge.org/
师兄您好,请问您运行data3dprepare.py共花了多长时间呀?我按您的代码,运行3天了,最后崩在了第154-179个生成文件上面是不是我是不是哪里出了问题呀?暂时没改变您在data3dprepare.py里面写的参数
您好,我之前用luna16数据集已经进行了肺结节的检测,检测结果是假阳性高,想用您的假阳性减少这一模块来去假阳。我看到ResNet3d_train.py这代码里面涉及到nodel_all_train.csv这一文件,但是我没有找到这一文件。请问是不能直接用去假阳这一模块吗?还是有什么解决办法呢?谢谢,祝好!
Hi @junqiangchen
Can you fix the link to download the trained model? Thank you so much.
Hello !
On what GPU did you run the training?
Thanks !
您好,在第四步遇到了一些疑惑想向您请教。1-3步顺利得到process文件夹,4看了您分享的已完成的csv文件内的路径,但我不知道如何获取segmentation文件夹,谢谢,祝好。
Hello,
Thanks for sharing your work. Are the 2 models meant to ensemble, chain or otherwise combine in some way? I am wondering how you use the Resnet to reduce FP in the Vnet mask output. Thanks!
您好,我阅读了您的文章并尝试了分类相关的程序,您提到的良恶性分类,然后实际上 0 代表非结节, 1 代表结节, 没有良恶性相关的区分,我有点困惑您提到的良恶性分类是如何做到的
我运行完程序,把您生成的bmp文件改为生成png图片,查看生成的结节mask,大约每个文件夹有一半是纯黑色图片,是有些是负样本吗
您好,感谢您的代码!但在运行分类代码的过程中遇到了无法生成分类文件0和1的问题,请问怎么解决?万分感激。
您好:
在data3prepare.py中,如果不想切出太多的sub_image,可以把numberxy=10, numberz=6
改成numberxy=3, numberz=20吗?
你好,我按照你的代码执行良恶数据处理后训练后loss一直在0.5-0.6几震荡,增加了epoch和BN层以及去除数据增强都没有作用,请问你在LUNA2022中得到的训练结果图是执行的这个代码吗?
In the ‘candidates.csv’, why is it that the nodule coordinates minus the origin coordinates get negative?
When I am using this method:
Vnet3d = Vnet3dModule(128, 128, 16, channels=1, costname=("dice coefficient",), inference=True,
model_path="/content/drive/MyDrive/model/resnet.pd-50000.data-00000-of-00001")
I got this error:
in init(self, image_height, image_width, image_depth, channels, costname, inference, model_path)
195 self.channels = channels
196
--> 197 self.X = tf.placeholder("float", shape=[None, self.image_depth, self.image_height, self.image_width,
198 self.channels])
199 self.Y_gt = tf.placeholder("float", shape=[None, self.image_depth, self.image_height, self.image_width,
AttributeError: module 'tensorflow' has no attribute 'placeholder'
请问在得到预测结果后,可以如何根据步长等参数对预测图片拼接成512*512的图片?
谢谢! @junqiangchen
No such file or directory: 'dataprocess\data\nodel_all_train.csv'
格式是哪样的?
Dear Sir, your work is helped me a lot in that I'm facing following problem,
please suggest how to run Augmain.py in spyder. when I run it showing following error:
File "D:\mywork\LUNA16 Master\Augmain.py", line 1, in
from dataaugmentation.Augmentation.ImageAugmentation import DataAug3D
ModuleNotFoundError: No module named 'dataaugmentation'
So, please provide the solution for above problem.
thank for advance
你好,正在学习相关内容,想问一下data3dprepare是如何获取(96,96,16)的patch的训练数据的
该模型是否可以在原图而不是子图预测出mask
Hello, it would be helpful if the paper presenting the work in this repo be cited here for reference.
Any elaboration would be much appreciated :) thanks in advance.
你好,我是一个初学者。在复现您的代码的时候,出现了一些问题,在训练Vnet模型时训练时间很短就结束了,Training_loss为-0.07308,请问可以给我一些建议吗。 还有一个疑问为什么要令Training_accuracy=-training_loss
陈老师,你好
我运行数据预处理部分的LUNA_node_extraction.py时,本来应该是生成classification文件夹的,但是我运行后没有结果。调试了一下代码发现line 93处的 if mini_df.shape[0] > 0: 这个判断都没有进去。尝试在此之前添加了一句print(mini_df.shape[0]),发现全部都是零。
多谢老师指教
我发现,如果我用全黑或者全白的图片放入您的V-net中进行检测,结果却显示有结节,这显然是不科学的,但我并不知道有什么问题,不知道您有尝试过吗?
I want to know how can we test a complete 3D image? If I have a 3D image (512512300), how to generate the nodule? Is there a such test code?
In addition, how to generate the confusion matrix and metrics?
您好,我复现了您的程序,觉得很有收获,只是有一个疑问就是您的loss = -dice,我觉得这里应该是1-dice。祝好。
如何为解决layer.py文件中“from ResNet3d.layer import (conv3d, normalizationlayer, max_pool3d, resnet_Add, weight_xavier_init, bias_variable, dense_to_one_hot)报错的问题”
I have trained your models. The results are good by your way.
But when I tested on dataset without segmentation techniques. The results for nodule class(label = 1) is very poor.
Do you think about it ? the test set should not be augmented.
I also want to download your trained models, but it is impossible with foreigners.
Why you do not upload on github ??
Thank you very much
Hello, when you run your program, you encounter some doubts. When I finished running Parts 1-3, I encountered difficulties in running Part 4. I don't know how to save the generated mask to the CSV file. Do you need to write your own code, or which Python file do you want to run? I hope to get your help.
Thank you.
Hello,
after evaluating the predictions file (i.e. METU_VISION_FPRED.csv) using the LUNA16 official script (i.e. noduleCADEvaluationLUNA16.py), I get an output (CADAnalysis.txt) like this :
CADAnalysis.txt
CAD Analysis: METU_VISION_FPRED
Candidate detection results:
True positives: 1128
False positives: 81706
False negatives: 58
True negatives: 0
Total number of candidates: 87794
Total number of nodules: 1186
Ignored candidates on excluded nodules: 4600
Ignored candidates which were double detections on a nodule: 360
Sensitivity: 0.951096121
Average number of candidates per scan: 98.867117117
From what I understand, the the Total number of candidates should be 754,975 according to https://luna16.grand-challenge.org/Evaluation/
Even though METU_VISION_FPRED.csv has 754,975 candidates!! the CADAnalysis.txt still says Total number of candidates: 87794 !!!!!
Looking forward to hearing back from you. Any help is extremely appreciated.
Many thanks.
Any idea why that happens?? Am I missing something?
请问在肺结节假阳性二分类的时候,代码结果是采用的了全部的结节数据集吗?因为我看到这个任务的正样本有1300+而负样本有5'000'000+
您好!正在复现您项目的分类部分,遇到了点问题,不是很理解subset.py文件的运行机理,
具体是里面的sys.argv[1]所对应的文件是什么?望解惑!感谢
您好,请问您的原始数据是怎么存放的,可以给出您数据的目录吗?
您好,在使用您提供的模型做segmeation预测时,产生了ValueError: cannot reshape array of size 16 into shape (16,96,96)问题,想请教您如何解决
Dear Sir thanks for your post it helped a lot. But I'm getting following issue when executing Vnet Training:
from Vnet.model_vnet3d import Vnet3dModule
ModuleNotFoundError: No module named 'Vnet'
I'm using Anacond in Windows.
So please suggest the solution for above issue
师兄您好,这几天我运行了一下您的程序,发现您更新了data3dprepare.py,但运行到
hr_samples[0, 0:blockz, 0:block_width, 0:block_height] = image[0:rangz, 0:rangwidth, 0:rangheight]
的时候报错,
TypeError: slice indices must be integers or None or have an index method
然后我发现rangz rangwidth rangheight 在前几行的计算过程得出的貌似不是整数型,
rangz = lambda imagez, blockz: imagez if imagez < blockz else blockz
rangwidth = lambda width, block_width: width if width < block_width else block_width
rangheight = lambda height, block_height: height if width < block_height else block_height
您看这里是不是需要int强制转换一下???
请问有没有pytorch版本的代码,十分感谢!!
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