First International Workshop on Artificial Intelligence over Infrared Images

Workshop Description

There have been many advances in medical infrared imaging hardware in recent years. Infrared imaging devices have improved in thermal sensitivity by orders of magnitude (0.8 to 0.02 deg C) in the last two decades and recent research explorations have unearthed multiple clinical use cases and medical applications for thermal imaging. This non-contact, non-invasive radiation-free low-cost portable modality offers several advantages over other imaging modalities to patient monitoring applications in general. Furthermore, since thermal images have some unique imaging characteristics with inbuilt anonymity and opportunity to analyze in both thermal and imaging feature space, it has sparked considerable interest in several research communities. A simple pubmed search with the combination of words ‘Thermal imaging ’ and ‘Medical’ results in over 5000 articles just in the last decade. This surge of applications is 10 times higher when compared to the publications on thermal imaging during 2000-2010. We are also starting to see innovative startups creating breakthrough solutions leveraging this emerging trend of advanced medical infrared thermology and use of novel machine learning algorithms over the captured thermal images. We believe it is time to create a forum to discuss this specific sub-topic at MICCAI and promote this novel area of research among the research community that has the potential to hugely impact our society.

Some specific clinical applications of Infrared Imaging are seen in screening, diagnosis and treatment of cancer, such as breast cancer, skin cancer, oral cancer and others. Utility in evaluating skeletomuscular issues such as rheumatoid arthritis, vascular complications such as detecting early onset of diabetic foot and river blindness (parasites under the skin) or even respiratory abnormalities such as pneumonia and COVID-19.  The patient monitoring applications include treatment monitoring during neoadjuvant chemotherapy, acupuncture, cryotherapy and pain management.  A focused discussion on the topic of machine analysis of  medical Infrared Imaging can help create new radiomic biomarkers that can help in several such clinical use cases. 

The research topics include but are not limited to novel machine learning and thermal image analysis algorithms for :

  1. Artificial intelligence for cancer screening and diagnosis 
  2. Artificial Intelligence for Treatment Monitoring
  3. Artificial Intelligence for health monitoring in public places
  4. Artificial Intelligence for patient monitoring with respiratory issues
  5. Thermal imaging with AI for COVID screening
  6. Artificial Intelligence for pain management
  7. Artificial Intelligence for veterinary medicine
  8. Artificial Intelligence for biomarkers prediction
  9. Thermal Surface Reconstruction / registration
  10. Thermal Image Segmentation
  11. 3D modeling 
  12. Image segmentation and cross-modality registration
  13. And others

Submission Guidelines

Submitted manuscripts must be in pdf format following formats available at Lecture Notes in Computer Science . Manuscripts should be at most 8 pages (content) + 2 pages (references and acknowledgements)

All accepted papers will be published as part of the MICCAI Satellite Events joint LNCS proceedings to be published by Springer Nature.

Important Dates

  • 25 June 2022 Paper submissions due
  • 16 July 2022 Notification of paper decisions
  • 30 July 2022 Camera ready papers due
  • 6 August 2022 Workshop proceedings due

Preliminary Program

Out of these, five will be full oral paper presentations  and five presentations would be in the form of  lighting talks. Each oral presentation duration would be 25 minutes (20 mins presentation + 5 minute QA) and lightning talk presentation would be 5 minutes. Along with the oral presentations, a one hour keynote session from eminent speakers will be conducted. This workshop will be planned for a half-day. Incase of significant high quality submissions, we will modify the agenda to reduce the oral presentation and accommodate 6 lighting talks of 5 minutes. 

Agenda

  • 8:00 – 8:15  Welcome note (Dr. Geetha Manjunath)
  • 8:15 – 9:15 Keynote session
  • 9:15 – 10:30 3 oral presentations (20 mins presentation + 5 minute QA)
  • 10:30 – 10:45 Break
  • 10:45 – 11:35 2 oral presentations (20 mins presentation + 5 minute QA)
  • 11:35-12:00 5 lightning presentation (5 mins each)
  • 12:00 – 12:30: Open Discussion

List of Open Source Thermal Datasets Available Online

Organizing Team

Prof. Alejandro F Frangi is Diamond Jubilee Chair in Computational Medicine and Royal Academy of Engineering Chair in Emerging Technologies at the University of Leeds. He was chair of the MICCAI Book Series editorial board and is associate editor for several journals. 

Dr. Geetha Manjunath is the Founder, CEO and CTO of NIRAMAI Health Analytix with a PhD and 25 years in industry. She was a chair for IEEE Computer Society Bangalore Chapter and has organized multiple research conferences and workshops..

Dr. Robert Schwartz is a clinician and an experienced thermologist. He has achieved numerous Board Certifications, published hundreds of articles, and has been guest professor at medical universities around the world. He is the chair  for American Academy of Thermology.

Dr. Siva Teja Kakileti has 6+ years of experience in AI for Medical Imaging. He is one of the founding members and principal research scientist at Niramai. He co-authored multiple international publications and has 16 international granted patents.