Congratulations to Dr. Subin Erattakulangara for a successful PhD defense. Thesis Title: Towards Accessible Deep Learning for Upper-Airway Segmentation: Open-Source Tool Development and Application in Voice and Sleep Apnea Studies Abstract: The human vocal tract is an integral part of our anatomy that enables essential functions such as speaking, singing, and breathing. To study and understand the vocal tract and the conditions affecting it, researchers utilize imaging techniques like magnetic resonance imaging (MRI), which offers detailed, non-invasive views of the vocal tract. The initial step in analyzing this data involves conducting manual segmentation, which is resource-intensive and time-consuming. In his thesis, Subin addresses these challenges in segmenting the upper airway by presenting various segmentation methods for multimodal MRI data that are both data-efficient and robust across different MRI protocols. Additionally, it includes the creation of open-source datasets with expert segmentations for 2D and 3D MRI scans as a contribution to the voice and speech community. The neural networks developed in his work are specifically modified to overcome the scarcity of large datasets in the realm of upper airway MRI. Furthermore, he has released a no-code tool called "AirSeg" to semi-automatically segment the upper airway, enabling experts to perform fast and efficient segmentation. Whats next: Subin is heading to NY to start a Research Scientist role in Dr. Ricardo Otazo and Dr. Victor Murray's labs at the Memorial Sloan Kettering Cancer Center. We wish him the best in this role.

Our work on zero-echo time MRI and vocal tract segmentation has been featured as the "cover art" for the 54th annual symposium of The Voice Foundation! The imagery showcases the registration of bony structures (skull, teeth) captured by zero-echo time MRI, along with the vocal tract segmented from a short, 10-second accelerated volume MRI scan during sustained phonation. Our long-term goal is to use such non-invasive imaging and modeling tools to better guide oropharyngeal surgical procedures involving the vocal apparatus (eg. cleft palate repair) We will be presenting this as an oral presentation at the symposium. This project is spearheaded by BME graduate student Swati Ramtilak and is in collaboration with Prof. David Meyer (Music, Communication Sciences and Disorders, Univ of Iowa), Prof. James Holmes (Radiology, Univ of Iowa), Prof. Aiming Lu (Radiology, Mayo Clinic).

Our article titled "Open-Source Manually Annotated Vocal Tract Database for Automatic Segmentation from 3D MRI Using Deep Learning: Benchmarking 2D and 3D Convolutional and Transformer Networks" has been accepted for publication at the Journal of Voice.

Congrats to Shahin, Wahid, Subin, and Silpa for their accepted abstracts at the ISMRM annual meeting in Honolulu, 2025

Congrats to Swati and Subin for their accepted abstracts as oral presentations at the 54th Annual Symposium: Care of the Professional Voice, Voice Foundation, June 2025. See below:

We celebrated the graduation of the first 2 PHD students from the lab. Congrats Dr. Wahid Alam and Dr. Rushdi Rusho!

Sajan Lingala to serve as a Guest Associate Editor for IEEE Transactions on Medical Imaging between 2025-2027.

Sajan Goud Lingala, assistant professor of biomedical engineering and radiology, is the principal investigator on the project.