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Development and performance evaluation of a deep learning lung nodule detection system

2024.02.08Publications

Lung cancer is one of the leading causes of cancer-related deaths. Chest CT is widely used to screen and diagnose lung cancer, but identifying small nodules is very burdensome and radiologists often miss them (Figure 1). In this paper [1], authors developed a computer-aided detection (CAD) system that automatically detects lung nodules in CT images using 3D convolutional neural network (Figure 2). The robustness of the CAD system to changes in radiation dose was evaluated by a phantom study, and the results showed that sensitivity did not change within the range of practical dose levels. In addition, reader performance test involving 10 doctors showed that the use of the CAD as a second reader could increase detection performance for nodules that require follow-up examinations. It is hoped that the CAD system will help more reliable management of lung cancer in the future.

Figure 1. An example of lung nodules.

Figure 2. Overview of the detection network. [1]
[1] Katase, S., Ichinose, A., Hayashi, M. et al. Development and performance evaluation of a deep learning lung nodule detection system. BMC Med Imaging 22, 203 (2022).

DOI: https://doi.org/10.1186/s12880-022-00938-8


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