Reliable Sarcoidosis Detection Using Chest X-rays with EfficientNets and Stain-Normalization Techniques

Sarcoidosis is frequently misdiagnosed as tuberculosis (TB) and consequently mistreated due to inherent limitations in radiological presentations. Clinically, to distinguish sarcoidosis from TB, physicians usually employ biopsy tissue diagnosis and blood tests; this approach is painful for patients,...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2022-05, Vol.22 (10), p.3846
Main Authors: Baghdadi, Nadiah, Maklad, Ahmed S, Malki, Amer, Deif, Mohanad A
Format: Article
Language:English
Subjects:
Blood
chest X-rays
Comparative analysis
Datasets
Diagnosis
Diagnostic systems
EfficientNets
Error analysis
Human error
Humans
Image classification
Medical care
Medical examination
Medical imaging
Methods
Model accuracy
Neural networks
Physicians
pulmonary sarcoidosis
Quality management
Radiography
Sarcoidosis - diagnostic imaging
sarcoidosis detection
stain normalization
Staining and Labeling
Tuberculosis
Tuberculosis, Pulmonary - diagnostic imaging
X-Rays
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Summary:Sarcoidosis is frequently misdiagnosed as tuberculosis (TB) and consequently mistreated due to inherent limitations in radiological presentations. Clinically, to distinguish sarcoidosis from TB, physicians usually employ biopsy tissue diagnosis and blood tests; this approach is painful for patients, time-consuming, expensive, and relies on techniques prone to human error. This study proposes a computer-aided diagnosis method to address these issues. This method examines seven EfficientNet designs that were fine-tuned and compared for their abilities to categorize X-ray images into three categories: normal, TB-infected, and sarcoidosis-infected. Furthermore, the effects of stain normalization on performance were investigated using Reinhard's and Macenko's conventional stain normalization procedures. This procedure aids in improving diagnostic efficiency and accuracy while cutting diagnostic costs. A database of 231 sarcoidosis-infected, 563 TB-infected, and 1010 normal chest X-ray images was created using public databases and information from several national hospitals. The EfficientNet-B4 model attained accuracy, sensitivity, and precision rates of 98.56%, 98.36%, and 98.67%, respectively, when the training X-ray images were normalized by the Reinhard stain approach, and 97.21%, 96.9%, and 97.11%, respectively, when normalized by Macenko's approach. Results demonstrate that Reinhard stain normalization can improve the performance of EfficientNet -B4 X-ray image classification. The proposed framework for identifying pulmonary sarcoidosis may prove valuable in clinical use.
ISSN:1424-8220
1424-8220
DOI:10.3390/s22103846