Search Results for author: Mehran Armand

Found 28 papers, 12 papers with code

Segment Any Medical Model Extended

1 code implementation26 Mar 2024 Yihao Liu, Jiaming Zhang, Andres Diaz-Pinto, Haowei Li, Alejandro Martin-Gomez, Amir Kheradmand, Mehran Armand

To this end, a unified platform helps push the boundary of the foundation model for medical images, facilitating the use, modification, and validation of SAM and its variants in medical image segmentation.

Data Augmentation Image Segmentation +3

Realtime Robust Shape Estimation of Deformable Linear Object

no code implementations24 Mar 2024 Jiaming Zhang, Zhaomeng Zhang, Yihao Liu, Yaqian Chen, Amir Kheradmand, Mehran Armand

We propose a robust method to estimate the shape of linear deformable objects in realtime using scattered and unordered key points.

Object Unity

A Roadmap Towards Automated and Regulated Robotic Systems

no code implementations21 Mar 2024 Yihao Liu, Mehran Armand

The rapid development of generative technology opens up possibility for higher level of automation, and artificial intelligence (AI) embodiment in robotic systems is imminent.

FluoroSAM: A Language-aligned Foundation Model for X-ray Image Segmentation

1 code implementation12 Mar 2024 Benjamin D. Killeen, Liam J. Wang, Han Zhang, Mehran Armand, Russell H. Taylor, Dave Dreizin, Greg Osgood, Mathias Unberath

Recently, foundation models (FMs) -- machine learning models trained on large amounts of highly variable data thus enabling broad applicability -- have emerged as promising tools for automated image analysis.

Image Segmentation Semantic Segmentation +1

Skin Lesion Correspondence Localization in Total Body Photography

1 code implementation18 Jul 2023 Wei-Lun Huang, Davood Tashayyod, Jun Kang, Amir Gandjbakhche, Michael Kazhdan, Mehran Armand

Longitudinal tracking of skin lesions - finding correspondence, changes in morphology, and texture - is beneficial to the early detection of melanoma.

SAMM (Segment Any Medical Model): A 3D Slicer Integration to SAM

1 code implementation12 Apr 2023 Yihao Liu, Jiaming Zhang, Zhangcong She, Amir Kheradmand, Mehran Armand

To assist with the development, assessment, and application of SAM on medical images, we introduce Segment Any Medical Model (SAMM), an extension of SAM on 3D Slicer - an image processing and visualization software extensively used by the medical imaging community.

Image Segmentation Segmentation +1

SyntheX: Scaling Up Learning-based X-ray Image Analysis Through In Silico Experiments

1 code implementation13 Jun 2022 Cong Gao, Benjamin D. Killeen, Yicheng Hu, Robert B. Grupp, Russell H. Taylor, Mehran Armand, Mathias Unberath

Here, we demonstrate that creating realistic simulated images from human models is a viable alternative and complement to large-scale in situ data collection.

Domain Generalization Lesion Segmentation

Generalizing Spatial Transformers to Projective Geometry with Applications to 2D/3D Registration

1 code implementation24 Mar 2020 Cong Gao, Xingtong Liu, Wenhao Gu, Benjamin Killeen, Mehran Armand, Russell Taylor, Mathias Unberath

We propose a novel Projective Spatial Transformer module that generalizes spatial transformers to projective geometry, thus enabling differentiable volume rendering.


From Perspective X-ray Imaging to Parallax-Robust Orthographic Stitching

no code implementations5 Mar 2020 Javad Fotouhi, Xingtong Liu, Mehran Armand, Nassir Navab, Mathias Unberath

Stitching images acquired under perspective projective geometry is a relevant topic in computer vision with multiple applications ranging from smartphone panoramas to the construction of digital maps.

Anatomy Image Stitching

Spatiotemporal-Aware Augmented Reality: Redefining HCI in Image-Guided Therapy

no code implementations4 Mar 2020 Javad Fotouhi, Arian Mehrfard, Tianyu Song, Alex Johnson, Greg Osgood, Mathias Unberath, Mehran Armand, Nassir Navab

Suboptimal interaction with patient data and challenges in mastering 3D anatomy based on ill-posed 2D interventional images are essential concerns in image-guided therapies.

Anatomy Management

Automatic Annotation of Hip Anatomy in Fluoroscopy for Robust and Efficient 2D/3D Registration

1 code implementation16 Nov 2019 Robert Grupp, Mathias Unberath, Cong Gao, Rachel Hegeman, Ryan Murphy, Clayton Alexander, Yoshito Otake, Benjamin McArthur, Mehran Armand, Russell Taylor

By using these annotations as training data for neural networks, state of the art performance in fluoroscopic segmentation and landmark localization was achieved.


Fast and Automatic Periacetabular Osteotomy Fragment Pose Estimation Using Intraoperatively Implanted Fiducials and Single-View Fluoroscopy

no code implementations22 Oct 2019 Robert Grupp, Ryan Murphy, Rachel Hegeman, Clayton Alexander, Mathias Unberath, Yoshito Otake, Benjamin McArthur, Mehran Armand, Russell Taylor

The relative pose of the fragment is established by estimating the movement of the two BB constellations using a single fluoroscopic view taken after osteotomy and fragment relocation.

Pose Estimation

Smooth Extrapolation of Unknown Anatomy via Statistical Shape Models

no code implementations23 Sep 2019 Robert Grupp, Hsin-Hong Chiang, Yoshito Otake, Ryan Murphy, Chad Gordon, Mehran Armand, Russell Taylor

The three extrapolation techniques evaluated were: copying and pasting of the surface estimate (non-smooth baseline), a feathering between the patient surface and surface estimate, and an estimate generated via a Thin Plate Spline trained from displacements between the surface estimate and corresponding vertices of the known patient surface.


Pelvis Surface Estimation From Partial CT for Computer-Aided Pelvic Osteotomies

no code implementations23 Sep 2019 Robert Grupp, Yoshito Otake, Ryan Murphy, Javad Parvizi, Mehran Armand, Russell Taylor

In order to reduce radiation exposure, we propose a new smooth extrapolation method leveraging a partial pelvis CT and a statistical shape model (SSM) of the full pelvis in order to estimate a patient's complete pelvis.


Patch-Based Image Similarity for Intraoperative 2D/3D Pelvis Registration During Periacetabular Osteotomy

1 code implementation23 Sep 2019 Robert Grupp, Mehran Armand, Russell Taylor

We use intensity-based 2D/3D registration to estimate the pelvis pose with respect to fluoroscopic images, recover relative poses of multiple views, and triangulate landmarks which may be used for navigation.

Learning to Detect Collisions for Continuum Manipulators without a Prior Model

no code implementations12 Aug 2019 Shahriar Sefati, Shahin Sefati, Iulian Iordachita, Russell H. Taylor, Mehran Armand

Due to their flexibility, dexterity, and compact size, Continuum Manipulators (CMs) can enhance minimally invasive interventions.

Reflective-AR Display: An Interaction Methodology for Virtual-Real Alignment in Medical Robotics

no code implementations23 Jul 2019 Javad Fotouhi, Tianyu Song, Arian Mehrfard, Giacomo Taylor, Qiaochu Wang, Fengfang Xian, Alejandro Martin-Gomez, Bernhard Fuerst, Mehran Armand, Mathias Unberath, Nassir Navab

To overcome this challenge, we introduce a novel registration concept for intuitive alignment of AR content to its physical counterpart by providing a multi-view AR experience via reflective-AR displays that simultaneously show the augmentations from multiple viewpoints.

Pose Estimation of Periacetabular Osteotomy Fragments with Intraoperative X-Ray Navigation

2 code implementations22 Mar 2019 Robert B. Grupp, Rachel A. Hegeman, Ryan J. Murphy, Clayton P. Alexander, Yoshito Otake, Benjamin A. McArthur, Mehran Armand, Russell H. Taylor

Results: In simulation, average fragment pose errors were 1. 3{\deg}/1. 7 mm when the planned fragment matched the intraoperative fragment, 2. 2{\deg}/2. 1 mm when the plan was not updated to match the true shape, and 1. 9{\deg}/2. 0 mm when the fragment shape was intraoperatively estimated.

Pose Estimation

Localizing dexterous surgical tools in X-ray for image-based navigation

2 code implementations20 Jan 2019 Cong Gao, Mathias Unberath, Russell Taylor, Mehran Armand

This manuscript describes a first step towards leveraging semantic information of the imaged object to initialize 2D/3D registration within the capture range of image-based registration by performing concurrent segmentation and localization of dexterous surgical tools in X-ray images.


Augmented Reality-based Feedback for Technician-in-the-loop C-arm Repositioning

no code implementations22 Jun 2018 Mathias Unberath, Javad Fotouhi, Jonas Hajek, Andreas Maier, Greg Osgood, Russell Taylor, Mehran Armand, Nassir Navab

For C-arm repositioning to a particular target view, the recorded C-arm pose is restored as a virtual object and visualized in an AR environment, serving as a perceptual reference for the technician.


Exploiting Partial Structural Symmetry For Patient-Specific Image Augmentation in Trauma Interventions

no code implementations9 Apr 2018 Javad Fotouhi, Mathias Unberath, Giacomo Taylor, Arash Ghaani Farashahi, Bastian Bier, Russell H. Taylor, Greg M. Osgood, M. D., Mehran Armand, Nassir Navab

The main challenge is to automatically estimate the desired plane of symmetry within the patient's pre-operative CT. We propose to estimate this plane using a non-linear optimization strategy, by minimizing Tukey's biweight robust estimator, relying on the partial symmetry of the anatomy.

Anatomy Image Augmentation

X-ray-transform Invariant Anatomical Landmark Detection for Pelvic Trauma Surgery

2 code implementations22 Mar 2018 Bastian Bier, Mathias Unberath, Jan-Nico Zaech, Javad Fotouhi, Mehran Armand, Greg Osgood, Nassir Navab, Andreas Maier

In this work, we present a method to automatically detect anatomical landmarks in X-ray images independent of the viewing direction.

Anatomy Decision Making +1

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