1 code implementation • 17 Mar 2024 • Shahabedin Nabavi, Kian Anvari Hamedani, Mohsen Ebrahimi Moghaddam, Ahmad Ali Abin, Alejandro F. Frangi
Besides, requiring bulk annotated data for model training, the large size of models, and the privacy-preserving of patients are other challenges of using DL in medical image classification.
1 code implementation • 22 Jul 2023 • Tara Gheshlaghi, Shahabedin Nabavi, Samire Shirzadikia, Mohsen Ebrahimi Moghaddam, Nima Rostampour
The dose distribution prediction subnet outperformed the winner of the OpenKBP2020 competition with 2. 77 and 1. 79 for dose and DVH scores, respectively.
no code implementations • 10 Apr 2023 • Mahsa Soleimani, Ali Nazari, Mohsen Ebrahimi Moghaddam
To test our approach, new datasets including real and fake images are created.
1 code implementation • 23 Mar 2023 • Shahabedin Nabavi, Hossein Simchi, Mohsen Ebrahimi Moghaddam, Ahmad Ali Abin, Alejandro F. Frangi
Methods: The proposed generalised deep meta-learning model can evaluate the quality by learning tasks in the prior stage and then fine-tuning the resulting model on a small labelled dataset of the desired tasks.
no code implementations • 18 Mar 2023 • Atefe Aghaei, Mohsen Ebrahimi Moghaddam
After extracting the ROIs automatically, Alzheimer's disease is predicted using extracted ROI-based 3D CNN.
no code implementations • 8 Feb 2023 • Mozhgan PourKeshavarz, Shahabedin Nabavi, Mohsen Ebrahimi Moghaddam, Mehrnoush Shamsfard
Thus, we propose a stacked cross-modal feature consolidation (SCFC) attention network for image captioning in which we simultaneously consolidate cross-modal features through a novel compounding function in a multi-step reasoning fashion.
no code implementations • 14 Jun 2022 • Shahabedin Nabavi, Mohammad Hashemi, Mohsen Ebrahimi Moghaddam, Ahmad Ali Abin, Alejandro F. Frangi
The accuracy of the baseline model in identifying the presence/absence of basal/apical slices is 96. 25\% and 94. 51\%, respectively, which increases to 96. 88\% and 95. 72\% after improving using the proposed salient region detection model.
no code implementations • 1 Feb 2022 • Razieh Ganjee, Mohsen Ebrahimi Moghaddam, Ramin Nourinia
Intra retinal fluids or Cysts are one of the important symptoms of macular pathologies that are efficiently visualized in OCT images.
no code implementations • 13 Dec 2021 • Shahabedin Nabavi, Hossein Simchi, Mohsen Ebrahimi Moghaddam, Alejandro F. Frangi, Ahmad Ali Abin
Increasing the speed of training and testing can be achieved with the proposed model in the frequency domain.
no code implementations • 1 Oct 2020 • Shahabedin Nabavi, Azar Ejmalian, Mohsen Ebrahimi Moghaddam, Ahmad Ali Abin, Alejandro F. Frangi, Mohammad Mohammadi, Hamidreza Saligheh Rad
The contribution of this study is four-fold: 1) to use as a tutorial of the field for both clinicians and technologists, 2) to comprehensively review the characteristics of COVID-19 as presented in medical images, 3) to examine automated artificial intelligence-based approaches for COVID-19 diagnosis based on the accuracy and the method used, 4) to express the research limitations in this field and the methods used to overcome them.
no code implementations • 17 Mar 2019 • Hassan Maleki Galandouz, Mohsen Ebrahimi Moghaddam, Mehrnoush Shamsfard
In this study, we present a method for visual retrieval based image captioning, in which we use a multi criteria decision making algorithm to effectively combine several criteria with proportional impact weights to retrieve the most relevant caption for the query image.
no code implementations • 24 Feb 2014 • Seyed Mostafa Kia, Hossein Rahmani, Reza Mortezaei, Mohsen Ebrahimi Moghaddam, Amer Namazi
To test the proposed method, performance of system was evaluated over 18354 download images from internet.