INTRODUCTION

This code project is for the paper Convolutional Neural Network-based Diagnostic Model for Solid, Indeterminate Solitary Pulmonary Nodule or Mass on Computed Tomography

The best model weights parameters are stored in the google drive.

Authors:

• Ke Sun¹, email: sk_peace@163.com
• Shouyu Chen ², email: 1910667@tongji.edu.cn
• Bin Wang¹
• Tingting Wang¹
• Yang Yang¹
• Yin Wang², email: yinw@tongji.edu.cn
• Chunyan Wu^3*
• Xiwen Sun^1*, email: sunxiwen5256@163.com

1. Department of Radiology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, 507 Zheng Min Road, Shanghai 200433, China.
2. Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, 4800 Cao'an Road, Shanghai, 201804, China.
3. Department of Pathology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, 507 Zheng Min Road, Shanghai 200433, China.

Dataset

Test Set Nodules

Node Size Statistics for Each Dataset

Results

Scores

	Training Set	Validation Set	Test Set
Accuracy	86.56%	80.43%	82.98%
AUC	94.66%	88.49%	91.17%
Recall	90.67%	82.14%	85.71%
Precision	87.50%	85.19%	85.71%

ROC curve

Confusion Matrix

Hotmap

hotmap on a benign nodule

hotmap on a malignant nodule