Acoustic and high-speed digital imaging based analysis of pathological voice contributes to better understanding and differential diagnosis of neurological dysphonias and of mimicking phonatory disorders. - Krzysztof Izdebski; Yuling Yan; Melda Kunduk (INTERSPEECH, 2009)

Glottis segmentation using dynamic programming. - Jing Chen; Bahadir K. Gunturk; Melda Kunduk (Image Processing, 2013)

Quantifying Spatiotemporal Properties of Vocal Fold Dynamics Based on a Multiscale Analysis of Phonovibrograms. - Jakob Unger; Dietmar J. Hecker; Melda Kunduk; Maria Schuster; Bernhard Schick; Jörg Lohscheller (IEEE Trans. Biomed. Eng., 2014)

Efficient Patient Orientation Detection in Videofluoroscopy Swallowing Studies. - Luisa Neubig; René Groh; Melda Kunduk; Deirdre Larsen; Rebecca Leonard; Andreas M. Kist (Bildverarbeitung für die Medizin, 2022)

Time-varying harmonic models for voice signal analysis. - Takeshi Ikuma; Andrew J. McWhorter; Lacey Adkins; Melda Kunduk (CoRR, 2022)

Markerless Tracking-Based Registration for Medical Image Motion Correction. - Luisa Neubig; Deirdre Larsen; Takeshi Ikuma; Markus Kopp; Melda Kunduk; Andreas M. Kist (GRAIL/RIME@MICCAI, 2025)

Machine learning based assessment of hoarseness severity: a multi-sensor approach centered on high-speed videoendoscopy. - Tobias Schraut; Anne Schützenberger; Tomás Arias-Vergara; Melda Kunduk; Matthias Echternach; Stephan Dürr; Julia Werz; Michael Döllinger (Frontiers Artif. Intell., 2025)

Comparison of fundamental frequency estimators with subharmonic voice signals. - Takeshi Ikuma; Melda Kunduk; Andrew J. McWhorter (CoRR, 2025)

Towards detecting the pathological subharmonic voicing with fully convolutional neural networks. - Takeshi Ikuma; Melda Kunduk; Brad Story; Andrew J. McWhorter (CoRR, 2025)