M
Masoud Nosrati
Researcher at Iowa State University
Publications - 85
Citations - 1040
Masoud Nosrati is an academic researcher from Iowa State University. The author has contributed to research in topics: Image segmentation & Steganography. The author has an hindex of 17, co-authored 84 publications receiving 882 citations. Previous affiliations of Masoud Nosrati include Islamic Azad University & Simon Fraser University.
Papers
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Journal ArticleDOI
Evaluation of Three Algorithms for the Segmentation of Overlapping Cervical Cells
Zhi Lu,Gustavo Carneiro,Andrew P. Bradley,Daniela Ushizima,Masoud Nosrati,Andrea Gomes Campos Bianchi,Cláudia Martins Carneiro,Ghassan Hamarneh +7 more
TL;DR: The first Overlapping Cervical Cytology Image Segmentation Challenge as discussed by the authors was organized to encourage the development and benchmarking of techniques capable of segmenting individual cells from overlapping cellular clumps in cervical cytology images.
Posted Content
Incorporating prior knowledge in medical image segmentation: a survey.
Masoud Nosrati,Ghassan Hamarneh +1 more
TL;DR: This survey focuses on optimization-based methods that incorporate prior information into their frameworks and reviews and compares these methods in terms of the types of prior employed, the domain of formulation, and the optimization techniques.
Journal Article
Investigation of the * (Star) Search Algorithms: Characteristics, Methods and Approaches - TI Journals
TL;DR: Features, basic concepts, algorithm and the approaches of each type of star algorithms is investigated separately in this paper.
Proceedings ArticleDOI
Segmentation of overlapping cervical cells: A variational method with star-shape prior
Masoud Nosrati,Ghassan Hamarneh +1 more
TL;DR: A new continuous variational segmentation framework with star-shape prior using directional derivatives to segment overlapping cervical cells in Pap smear images is proposed and it is shown that the star- shape constraint better models the underlying problem and outperforms state-of-the-art methods in terms of accuracy and speed.
Journal ArticleDOI
Simultaneous Multi-Structure Segmentation and 3D Nonrigid Pose Estimation in Image-Guided Robotic Surgery
Masoud Nosrati,Rafeef Abugharbieh,Jean-Marc Peyrat,Julien Abinahed,Osama Al-Alao,Abdulla Al-Ansari,Ghassan Hamarneh +6 more
TL;DR: This paper proposes a multi-modal approach to segmentation where preoperative 3D computed tomography scans and intraoperative stereo-endoscopic video data are jointly analyzed and estimates and track the pose of the preoperative models in 3D and consider the models' non-rigid deformations to match with corresponding visual cues in multi-channel endoscopic video and segment the objects of interest.