1. Light emitting diodes, an alternative excitation source for photoacoustic imaging (Thomas Allen, Paul Beard et al , UCL, United Kingdom)
2. LED-based Photoacoustic imaging in imaging human inflammatory arthritis (Xueding Wang et al, Michigan University, USA)
3. LED-based photoacoustic evaluation method for Port-wine Stain and its curative effect - clinical pilot study (Qian Cheng
et al, Tongji University, China)
4. LED-based photoacoustics - portable and affordable solution for functional preclinical imaging (Srivalleesha Mallidi et al, Harvard Medical School/Tufts University, USA)
5. LED-based photoacoustic imaging of human peripheral vasculature and minimally invasive devices (Adrien Desjardins
et al, UCL, United Kingdom)
6. Structural, functional and molecular imaging capabilities of a dual-mode LED-based photoacoustic and ultrasound imaging system (Sri-Rajasekhar Kothapalli et al, The Pennsylvania State University, USA)
7. Democratizing LED-based photoacoustic imaging using adaptive beamforming and deep convolutional neural network (Haichong Zhang, Emad Boctor
et al, Worcester Polytechnic Institute/ Johns Hopkins University, USA)
8. Potential of LED-based photoacoustic imaging in guiding lymphaticovenous anastomosis: A human volunteer study ( Mithun Kuniyil Ajith Singh et al, CYBERDYNE, INC, The Netherlands / Saga University Hospital, Japan)
9. Data structure assisted accelerated reconstruction strategy for handheld photoacoustic imaging (Samir Kumar Biswas et al, IISER Mohali, India)
10. Deep low-energy handheld photoacoustic imaging via extensive motion-compensated averaging (Michael Jaeger, Martin Frenz et al, University of Bern, Switzerland)
11. Deep learning for image processing and reconstruction to enhance SNR of LED based photoacoustic imaging (Kathyayini Sivasubramanian
et al, Stanford University, USA)
12. Multiscale signal processing methods for improving image reconstruction and visual quality in LED based photoacoustic systems (Kausik Basak and Subhamoy Mandal, IIT Kharagpur, India/ DFKZ, Heidelberg, Germany)
13. Clinical translation of photoacoustic imaging - opportunities and challenges from an industry perspective (Mithun Kuniyil Ajith Singh
et al, CYBERDYNE INC, The Netherlands)
Dr. Mithun Kuniyil Ajith Singh is an engineering scientist with extensive experience in preclinical and clinical photoacoustic and ultrasound imaging. He is presently working as a Research and Business Development Manager at CYBERDYNE, INC, the Netherlands. In his current role, he initiates and coordinates various scientific projects in collaboration with globally renowned research groups, especially focusing on the clinical translation of LED-based photoacoustic imaging technology. Mithun received his Technical Diploma in Medical Electronics from Model Polytechnic College, Calicut, India, in 2004; his Bachelor's degree in Biomedical Instrumentation and Engineering from SRM University, Chennai, India, in 2008; and his Master's degree in Bio-photonics from the École normale supérieure de Cachan, France, in 2012. From January 2013 to December 2016, he pursued research for his Ph.D. thesis at the Biomedical Photonic Imaging Group, University of Twente, the Netherlands, under thesupervision of Professor Wiendelt Steenbergen.
While working on his Ph.D., he invented a new method called PAFUSion (photoacoustic-guided focused ultrasound) for reducing reflection artifacts and improving contrast and imaging depth in photoacoustic imaging, and demonstrated its potential in clinical pilot studies. Mithun has published over 40 international journal articles and conference proceedings papers. He won the Seno Medical Best Paper Award at the annual conference 'Photons plus Ultrasound: Imaging and Sensing' during the SPIE Photonics West 2016 event in San Francisco. As one of many academic achievements and scholarships, SRM University, India, presented him with a Commendation Award for his outstanding contributions to the field of biomedical engineering in 2017. Mithun is currently serving as a reviewer for several leading journals in the field of optics and won Elsevier's Outstanding Reviewer Award in 2018.
