Search Results for author: Reza Azad

Found 45 papers, 28 papers with code

Continual Learning in Medical Image Analysis: A Comprehensive Review of Recent Advancements and Future Prospects

no code implementations28 Dec 2023 Pratibha Kumari, Joohi Chauhan, Afshin Bozorgpour, Boqiang Huang, Reza Azad, Dorit Merhof

Medical imaging analysis has witnessed remarkable advancements even surpassing human-level performance in recent years, driven by the rapid development of advanced deep-learning algorithms.

Continual Learning

Loss Functions in the Era of Semantic Segmentation: A Survey and Outlook

1 code implementation8 Dec 2023 Reza Azad, Moein Heidary, Kadir Yilmaz, Michael Hüttemann, Sanaz Karimijafarbigloo, Yuli Wu, Anke Schmeink, Dorit Merhof

Semantic image segmentation, the process of classifying each pixel in an image into a particular class, plays an important role in many visual understanding systems.

Image Segmentation Segmentation +1

Leveraging Unlabeled Data for 3D Medical Image Segmentation through Self-Supervised Contrastive Learning

no code implementations21 Nov 2023 Sanaz Karimijafarbigloo, Reza Azad, Yury Velichko, Ulas Bagci, Dorit Merhof

Current 3D semi-supervised segmentation methods face significant challenges such as limited consideration of contextual information and the inability to generate reliable pseudo-labels for effective unsupervised data use.

Contrastive Learning Image Segmentation +3

INCODE: Implicit Neural Conditioning with Prior Knowledge Embeddings

1 code implementation28 Oct 2023 Amirhossein Kazerouni, Reza Azad, Alireza Hosseini, Dorit Merhof, Ulas Bagci

INCODE comprises a harmonizer network and a composer network, where the harmonizer network dynamically adjusts key parameters of the activation function.

Denoising Image Inpainting +1

Foundational Models in Medical Imaging: A Comprehensive Survey and Future Vision

1 code implementation28 Oct 2023 Bobby Azad, Reza Azad, Sania Eskandari, Afshin Bozorgpour, Amirhossein Kazerouni, Islem Rekik, Dorit Merhof

Foundation models, large-scale, pre-trained deep-learning models adapted to a wide range of downstream tasks have gained significant interest lately in various deep-learning problems undergoing a paradigm shift with the rise of these models.

Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentation

1 code implementation31 Aug 2023 Reza Azad, Leon Niggemeier, Michael Huttemann, Amirhossein Kazerouni, Ehsan Khodapanah Aghdam, Yury Velichko, Ulas Bagci, Dorit Merhof

To address these challenges, we introduce the concept of \textbf{Deformable Large Kernel Attention (D-LKA Attention)}, a streamlined attention mechanism employing large convolution kernels to fully appreciate volumetric context.

Image Segmentation Medical Image Segmentation +1

Unlocking Fine-Grained Details with Wavelet-based High-Frequency Enhancement in Transformers

2 code implementations25 Aug 2023 Reza Azad, Amirhossein Kazerouni, Alaa Sulaiman, Afshin Bozorgpour, Ehsan Khodapanah Aghdam, Abin Jose, Dorit Merhof

Furthermore, to intensify the importance of the boundary information, we impose an additional attention map by creating a Gaussian pyramid on top of the HF components.

Image Segmentation Lesion Segmentation +3

Implicit Neural Representation in Medical Imaging: A Comparative Survey

1 code implementation30 Jul 2023 Amirali Molaei, Amirhossein Aminimehr, Armin Tavakoli, Amirhossein Kazerouni, Bobby Azad, Reza Azad, Dorit Merhof

Recognizing the potential of INRs beyond these domains, this survey aims to provide a comprehensive overview of INR models in the field of medical imaging.

Domain Adaptation Image Reconstruction +1

Enhancing Medical Image Segmentation with TransCeption: A Multi-Scale Feature Fusion Approach

1 code implementation25 Jan 2023 Reza Azad, Yiwei Jia, Ehsan Khodapanah Aghdam, Julien Cohen-Adad, Dorit Merhof

(3) In contrast to a bridge that only contains token-wise self-attention, we propose a Dual Transformer Bridge that also includes channel-wise self-attention to exploit correlations between scales at different stages from a dual perspective.

Image Segmentation Lesion Segmentation +3

Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Review

1 code implementation9 Jan 2023 Reza Azad, Amirhossein Kazerouni, Moein Heidari, Ehsan Khodapanah Aghdam, Amirali Molaei, Yiwei Jia, Abin Jose, Rijo Roy, Dorit Merhof

The remarkable performance of the Transformer architecture in natural language processing has recently also triggered broad interest in Computer Vision.

Diffusion Models for Medical Image Analysis: A Comprehensive Survey

1 code implementation14 Nov 2022 Amirhossein Kazerouni, Ehsan Khodapanah Aghdam, Moein Heidari, Reza Azad, Mohsen Fayyaz, Ilker Hacihaliloglu, Dorit Merhof

Then, we provide a systematic taxonomy of diffusion models in the medical domain and propose a multi-perspective categorization based on their application, imaging modality, organ of interest, and algorithms.

Denoising Navigate

Attention Swin U-Net: Cross-Contextual Attention Mechanism for Skin Lesion Segmentation

1 code implementation30 Oct 2022 Ehsan Khodapanah Aghdam, Reza Azad, Maral Zarvani, Dorit Merhof

We argue that the classical concatenation operation utilized in the skip connection path can be further improved by incorporating an attention mechanism.

Image Segmentation Lesion Segmentation +3

TransDeepLab: Convolution-Free Transformer-based DeepLab v3+ for Medical Image Segmentation

1 code implementation1 Aug 2022 Reza Azad, Moein Heidari, Moein Shariatnia, Ehsan Khodapanah Aghdam, Sanaz Karimijafarbigloo, Ehsan Adeli, Dorit Merhof

Especially, deep neural networks based on seminal architectures such as U-shaped models with skip-connections or atrous convolution with pyramid pooling have been tailored to a wide range of medical image analysis tasks.

Image Segmentation Medical Image Segmentation +1

TransNorm: Transformer Provides a Strong Spatial Normalization Mechanism for a Deep Segmentation Model

1 code implementation27 Jul 2022 Reza Azad, Mohammad T. AL-Antary, Moein Heidari, Dorit Merhof

In the past few years, convolutional neural networks (CNNs), particularly U-Net, have been the prevailing technique in the medical image processing era.

Image Segmentation Medical Image Segmentation +2

Intervertebral Disc Labeling With Learning Shape Information, A Look Once Approach

no code implementations6 Apr 2022 Reza Azad, Moein Heidari, Julien Cohen-Adad, Ehsan Adeli, Dorit Merhof

Accurate and automatic segmentation of intervertebral discs from medical images is a critical task for the assessment of spine-related diseases such as osteoporosis, vertebral fractures, and intervertebral disc herniation.

SMU-Net: Style matching U-Net for brain tumor segmentation with missing modalities

1 code implementation6 Apr 2022 Reza Azad, Nika Khosravi, Dorit Merhof

Gliomas are one of the most prevalent types of primary brain tumours, accounting for more than 30\% of all cases and they develop from the glial stem or progenitor cells.

Brain Tumor Segmentation Tumor Segmentation

Medical Image Segmentation on MRI Images with Missing Modalities: A Review

no code implementations11 Mar 2022 Reza Azad, Nika Khosravi, Mohammad Dehghanmanshadi, Julien Cohen-Adad, Dorit Merhof

Dealing with missing modalities in Magnetic Resonance Imaging (MRI) and overcoming their negative repercussions is considered a hurdle in biomedical imaging.

Image Generation Image Segmentation +3

Contextual Attention Network: Transformer Meets U-Net

2 code implementations2 Mar 2022 Reza Azad, Moein Heidari, Yuli Wu, Dorit Merhof

Then, they emphasize the informative regions while taking into account the long-range contextual dependency derived by the Transformer module.

Image Segmentation Medical Image Segmentation +2

Stacked Hourglass Network with a Multi-level Attention Mechanism: Where to Look for Intervertebral Disc Labeling

1 code implementation14 Aug 2021 Reza Azad, Lucas Rouhier, Julien Cohen-Adad

To further improve the performance of the proposed method, we propose a skeleton-based search space to reduce false positive detection.

Pose Estimation Semantic Segmentation

Semi-supervised few-shot learning for medical image segmentation

no code implementations18 Mar 2020 Abdur R Feyjie, Reza Azad, Marco Pedersoli, Claude Kauffman, Ismail Ben Ayed, Jose Dolz

To handle this new learning paradigm, we propose to include surrogate tasks that can leverage very powerful supervisory signals --derived from the data itself-- for semantic feature learning.

Few-Shot Learning Image Segmentation +4

Multi-level Context Gating of Embedded Collective Knowledge for Medical Image Segmentation

1 code implementation10 Mar 2020 Maryam Asadi-Aghbolaghi, Reza Azad, Mahmood Fathy, Sergio Escalera

These blocks adaptively recalibrate the channel-wise feature responses by utilizing a self-gating mechanism of the global information embedding of the feature maps.

Anatomy Image Segmentation +3

On the Texture Bias for Few-Shot CNN Segmentation

1 code implementation9 Mar 2020 Reza Azad, Abdur R Fayjie, Claude Kauffman, Ismail Ben Ayed, Marco Pedersoli, Jose Dolz

Despite the initial belief that Convolutional Neural Networks (CNNs) are driven by shapes to perform visual recognition tasks, recent evidence suggests that texture bias in CNNs provides higher performing models when learning on large labeled training datasets.

Few-Shot Semantic Segmentation Segmentation +1

Real-Time Human-Computer Interaction Based on Face and Hand Gesture Recognition

no code implementations7 Aug 2014 Reza Azad, Babak Azad, Nabil Belhaj Khalifa, Shahram Jamali

In the proposed technique, first, the hand gesture and face location is extracted from the main image by combination of skin and cascade detector and then is sent to recognition stage.

Face Recognition Hand Gesture Recognition +1

Real-Time and Efficient Method for Accuracy Enhancement of Edge Based License Plate Recognition System

no code implementations24 Jul 2014 Reza Azad, Babak Azad, Hamid Reza Shayegh

This method has been tested on available data set that has different images of the background, considering distance, and angel of view so that the correct extraction rate of plate reached at 98% and character recognition rate achieved at 99. 12%.

Edge Detection License Plate Recognition +1

Novel and Tuneable Method for Skin Detection Based on Hybrid Color Space and Color Statistical Features

no code implementations24 Jul 2014 Reza Azad, Hamid Reza Shayegh

In the first one, from pure skin statistical features were extracted and at the second stage, the skin pixels are detected using HSV and YCbCr color spaces.

Face Detection

Recognition of Handwritten Persian/Arabic Numerals Based on Robust Feature Set and K-NN Classifier

no code implementations24 Jul 2014 Reza Azad, Fatemeh Davami, Hamid Reza Shayegh

This paper has been withdrawn by the author due to a crucial sign error in equation 2 and some mistake in Table 1 information.

Novel and Fast Algorithm for Extracting License Plate Location Based on Edge Analysis

no code implementations24 Jul 2014 Reza Azad, Mohammad Baghdadi

Nowadays in developing or developed countries, the Intelligent Transportation System (ITS) technology has attracted so much attention to itself.

Edge Detection License Plate Recognition

Novel and Automatic Parking Inventory System Based on Pattern Recognition and Directional Chain Code

no code implementations23 Jul 2014 Reza Azad, Majid Nazari

The system is then allowed to open parking barrier for the vehicle and generate entrance cost receipt.

License Plate Recognition

A robust and adaptable method for face detection based on Color Probabilistic Estimation Technique

no code implementations23 Jul 2014 Reza Azad, Fatemeh Davami

In the first one, the skin intensity distribution is estimated using some train photos of pure skin, and at the second stage, the skin pixels are detected using Gaussian model and optimal threshold tuning.

Face Detection

Optimized Method for Iranian Road Signs Detection and recognition system

no code implementations20 Jul 2014 Reza Azad, Babak Azad, Iman Tavakoli Kazerooni

Road sign recognition is one of the core technologies in Intelligent Transport Systems.

Edge Detection

Classifiers fusion method to recognize handwritten persian numerals

no code implementations9 Jul 2014 Reza Azad, Babak Azad, Iraj Mogharreb, Shahram Jamali

For evaluation of the proposed method we considered a Persian numerals database with 20, 000 handwritten samples.

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