Real-time monitoring of patients is critical for recognizing oscillations in their health status, allowing for the prediction and avoidance of potential consequences. Certain medical procedures, such as transbronchial biopsy and mechanical ventilation, can cause unintended air leakage into the pleural space, resulting in pneumothorax, which can worsen the patient’s clinical condition if not detected quickly. Electrical impedance tomography (EIT) is an imaging technique that excels in real-time monitoring of aerated tissues like the lungs, allowing for the tracking of pneumothorax progression and localization. Despite EIT’s significant association with regional air content variations, its images frequently have low spatial resolution. To address this limitation, the utilization of an anatomical atlas as a regularization method is proposed to enhance image quality. To assess the effect of adding the anatomical atlas on pneumothorax detection performance, an algorithm was used to calculate pneumothorax duration and detection time. The purpose of this study was to analyze the performance of the pneumothorax identification algorithm when images were used with and without the anatomical atlas. The results show that for atlas weights up to 4, there were minor discrepancies in measured time intervals of no more than 2%.