Photoacoustic imaging aided with deep learning: a review

• المؤلفون الرئيسيون: Rajendran, Praveenbalaji, Sharma, Arunima, Pramanik, Manojit
• مؤلفون آخرون: School of Chemical and Biomedical Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2022
• الموضوعات: Engineering::Bioengineering; Photoacoustic Tomography; Photoacoustic Microscopy
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/157117
• المؤسسة: Nanyang Technological University

Photoacoustic imaging (PAI) is an emerging hybrid imaging modality integrating the benefits of both optical and ultrasound imaging. Although PAI exhibits superior imaging capabilities, its translation into clinics is still hindered by various limitations. In recent years, deeplearning (DL), a new paradigm of machine learning, is gaining a lot of attention due to its ability to improve medical images. Likewise, DL is also widely being used in PAI to overcome some of the limitations of PAI. In this review, we provide a comprehensive overview on the various DL techniques employed in PAI along with its promising advantages.