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Ali Khamene

Researcher at Princeton University

Publications -  42
Citations -  2526

Ali Khamene is an academic researcher from Princeton University. The author has contributed to research in topics: Image registration & Augmented reality. The author has an hindex of 25, co-authored 42 publications receiving 2432 citations. Previous affiliations of Ali Khamene include University of Miami.

Papers
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Journal ArticleDOI

The FLARE™ Intraoperative Near-Infrared Fluorescence Imaging System: A First-in-Human Clinical Trial in Breast Cancer Sentinel Lymph Node Mapping

TL;DR: Simultaneous pan-lymphatic and SLN mapping was demonstrated in swine using clinically available NIR fluorophores and the dual NIR capabilities of the FLARE™ system, describing the successful clinical translation of a new NIR fluorescence imaging system for image-guided oncologic surgery.
Journal ArticleDOI

Automatic CT-ultrasound registration for diagnostic imaging and image-guided intervention

TL;DR: New methods that allow one to simulate medical ultrasound from CT in real-time, reproducing the majority of ultrasonic imaging effects are developed, along with a robust similarity measure.
Journal ArticleDOI

Automatic registration of portal images and volumetric CT for patient positioning in radiation therapy

TL;DR: This work proposes and evaluates an intensity based automatic registration method using multiple portal images and the pre-treatment CT volume, and performs both geometric and radiometric calibrations to generate high quality digitally reconstructed radiographs (DRRs) that can be compared against portal images acquired right before treatment dose delivery.
Patent

Method and apparatus for ultrasound guidance of needle biopsies

TL;DR: In this article, an ultrasound scanning system has an ultrasound transducer (10) which provides ultrasound images, a computer to process the ultrasound information and to render the ultrasound image correctly positioned and scaled for display on a flat panel monitor (29) which has a display size similar to the actual physical size of the image.
Book ChapterDOI

Simulation and fully automatic multimodal registration of medical ultrasound

TL;DR: New methods that allow one to simulate medical ultrasound from CT in real-time, reproducing the majority of ultrasonic imaging effects, and a robust similarity measure that assesses the correlation of a combination of multiple signals extracted from CT with ultrasound.