Author

A. Ahmadian

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Bioengineering· 5

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:deep learning· 5 Assay:imaging· 5 Research Focus:clustering· 4 Approach:transformer / foundation model· 3 Research Focus:cell type annotation· 2 Research Focus:dimensionality reduction· 2 Organism:human· 2 Research Focus:benchmarking· 1

Frequent Co-Authors

P. Farnia· 3 shared A. Amiri Tehrani Zade· 2 shared M. Alimohammadi· 2 shared M. Jalili Aziz· 2 shared A. H. Davarpanah· 1 shared A. Mirbagheri· 1 shared A. Radmard· 1 shared A. Salehnia· 1 shared

Activity by Year

2021-2022 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersBioengineering

P. Farnia

Mutual co-authors in cluster

Author profile →

5 papers

Recent·Most cited

Spatiotemporal analysis of speckle dynamics to track invisible needle in ultrasound sequences using Convolutional Neural Networks

A. Amiri Tehrani Zade, M. Jalili Aziz, H. Majedi, A. Mirbagheri, A. Ahmadian

This paper develops a CNN-based framework to track invisible needles in ultrasound sequences using spatiotemporal features of speckle dynamics, achieving accurate localization in challenging conditions.

bioRxiv · Aug 2, 2022 · PreprintBioengineering

D2BGAN: Dual Discriminator Bayesian Generative Adversarial Network for Deformable MR-Ultrasound Registration Applied to Brain Shift compensation

M. Rahmani, H. Moghadssi, P. Farnia, A. Ahmadian

This paper introduces D2BGAN, a dual discriminator Bayesian GAN for MR-ultrasound registration, achieving improved accuracy in brain shift compensation with a mean TRE of 0.75 mm.

bioRxiv · Jan 22, 2022Bioengineering

Photoacoustic-MR Images Registration Based on Co-Sparse Analysis Model to Compensate for Brain Shift

P. Farnia, B. Makkiiabadi, M. Alimohammadi, E. Najafzadeh, M. Basij, Y. Yan, M. Mehrmohammadi, A. Ahmadian

This study proposes a co-sparse analysis model for registering intra-operative photoacoustic images with pre-operative MR images to improve brain shift compensation in neurosurgery.

bioRxiv · Jul 28, 2021Bioengineering

Accurate Automatic Glioma Segmentation in Brain MRI images Based on CapsNet

M. Jalili Aziz, A. Amiri Tehrani Zade, P. Farnia, M. Alimohammadi, B. Makki Abadi, A. Ahmadian, J. Alirezaie

This paper introduces SegCaps, a capsule network for glioma segmentation in MRI images, achieving higher accuracy with fewer data and parameters than U-Net.

bioRxiv · Jul 3, 2021 · PreprintBioengineering

Segmentation of Pancreatic Ductal Adenocarcinoma (PDAC) and surrounding vessels in CT images using deep convolutional neural networks and Texture Descriptors

T. Mahmoudi, Z. Mousavi Kouzehkanan, A. Radmard, R. Kafieh, A. Salehnia, A. H. Davarpanah, H. Arabalibeik, A. Ahmadian

This paper proposes a deep learning framework for automated segmentation of PDAC and surrounding vessels in CT images, achieving improved Dice scores using 3D-CNN and texture descriptors.

bioRxiv · Jun 9, 2021Bioengineering