Haseeb Hassan

Haseeb Hassan
Verified
Haseeb verified their affiliation via an institutional email.
Verified
Haseeb verified their affiliation via an institutional email.
Shenzhen Technology University

Ph.D Computer Science

About

38
Publications
13,004
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
421
Citations
Additional affiliations
January 2021 - present
Shenzhen University
Position
  • Research Associate Professor
September 2016 - July 2019
Anhui University
Position
  • Researcher

Publications

Publications (38)
Article
Full-text available
Objective The precise segmentation of kidneys from a 2D ultrasound (US) image is crucial for diagnosing and monitoring kidney diseases. However, achieving detailed segmentation is difficult due to US images’ low signal-to-noise ratio and low-contrast object boundaries. Methods This paper presents an approach called deep supervised attention with m...
Article
Full-text available
Ischemic stroke is a leading global cause of death and disability and is expected to rise in the future. The present diagnostic techniques, like CT and MRI, have some limitations in distinguishing acute from chronic ischemia and in early ischemia detection. This study investigates the function of ensemble models based on the dynamic radiomics featu...
Article
Predicting long-term clinical outcomes based on the early DSC PWI MRI scan is valuable for prognostication, resource management, clinical trials, and patient expectations. Current methods require subjective decisions about which imaging features to assess and may require time-consuming postprocessing. This study’s goal was to predict multilabel 90-...
Article
Full-text available
COVID-19 is a worldwide epidemic that seriously affected the lives of people. Since its inception, physicians have tried their best to trace the virus and reduce its spread. Several diagnostic approaches have been reported to detect the coronavirus in research, clinical, and public health laboratories. Although the existing systems aid medical expe...
Article
Full-text available
Introduction Accurate neurological impairment assessment is crucial for the clinical treatment and prognosis of patients with acute ischemic stroke (AIS). However, the original perfusion parameters lack the deep information for characterizing neurological impairment, leading to difficulty in accurate assessment. Given the advantages of radiomics te...
Article
Full-text available
While deep learning technologies have made remarkable progress in generating deepfakes, their misuse has become a well-known concern. As a result, the ubiquitous usage of deepfakes for increasing false information poses significant risks to the security and privacy of individuals. The primary objective of audio spoofing detection is to identify aud...
Article
Full-text available
Diagnosing liver disease presents a significant medical challenge in impoverished countries, with over 30 billion individuals succumbing to it each year. Existing models for detecting liver abnormalities suffer from lower accuracy and higher constraint metrics. As a result, there is a pressing need for improved, efficient, and effective liver disea...
Article
Full-text available
Introduction In neurological diagnostics, accurate detection and segmentation of brain lesions is crucial. Identifying these lesions is challenging due to its complex morphology, especially when using traditional methods. Conventional methods are either computationally demanding with a marginal impact/enhancement or sacrifice fine details for compu...
Article
Full-text available
Spoofed speeches are becoming a big threat to society due to advancements in artificial intelligence techniques. Therefore, there must be an automated spoofing detector that can be integrated into automatic speaker verification (ASV) systems. In this study, we recommend a novel and robust model, named DeepDet, based on deep-layered architecture, to...
Article
Full-text available
Detecting and accurately locating kidney stones, which are common urological conditions, can be challenging when using imaging examinations. Therefore, the primary objective of this research is to develop an ensemble model that integrates segmentation and registration techniques. This model aims to visualize the inner structure of the kidney and ac...
Article
Full-text available
Chronic obstructive pulmonary disease (COPD) is a common lung disease that can lead to restricted airflow and respiratory problems, causing a significant health, economic, and social burden. Detecting the COPD stage can provide a timely warning for prompt intervention in COPD patients. However, existing methods based on inspiratory (IN) and expirat...
Conference Paper
This research proposes a weakly supervised-based learning registration network called Improved Transformer Registration Net (ITR-Net) to improve medical image registration accuracy. Firstly, we improved the transformer module by incorporating patch embedding and a feed-forward layer. These enhancements enable the transformer module to focus on loca...
Conference Paper
Object detection is the main task in computer vision. Recently, object detection tasks have been performed through convolutional neural networks and the YOLO family, and gained substantial attention from the research community. Likewise, transformer-based models were introduced to improve the efficiency and accuracy of many detection models. Howeve...
Preprint
Full-text available
Facial emotion detection is a challenging task that deals with emotion recognition. It has applications in various domains, such as behavior analysis, surveillance systems and human-computer interaction (HCI). Numerous studies have been implemented to detect emotions, including classical machine learning algorithms and advanced deep learning algori...
Preprint
Full-text available
Bayesian inference has many advantages in robotic motion planning over four perspectives: The uncertainty quantification of the policy, safety (risk-aware) and optimum guarantees of robot motions, data-efficiency in training of reinforcement learning, and reducing the sim2real gap when the robot is applied to real-world tasks. However, the applicat...
Article
Full-text available
Cerebrovascular and airway structures are tubular structures used for transporting blood and gases, respectively, providing essential support for the normal activities of the human body. Accurately segmenting these tubular structures is the basis of morphology research and pathological detection. Nevertheless, accurately segmenting these structures...
Chapter
Full-text available
Large curated datasets are necessary, but annotating medical images is a time-consuming, laborious, and expensive process. Therefore, recent supervised methods are focusing on utilizing a large amount of unlabeled data. However, to do so, is a challenging task. To address this problem, we propose a new 3D Cross-Pseudo Supervision (3D-CPS) method, a...
Article
Full-text available
Robotic motion planning in dense and dynamic indoor scenarios constantly challenges the researchers because of the motion unpredictability of obstacles. Recent progress in reinforcement learning enables robots to better cope with the dense and unpredictable obstacles by encoding complex features of the robot and obstacles into the encoders like the...
Article
Full-text available
Recent breakthroughs of deep learning algorithms in medical imaging, automated detection , and segmentation techniques for renal (kidney) in abdominal computed tomography (CT) images have been limited. Radiomics and machine learning analyses of renal diseases rely on the automatic segmentation of kidneys in CT images. Inspired by this, our primary...
Article
Full-text available
Most deep-learning-based vision models are trained and tested on clear images, avoiding noisy, or hazy, images. However, these models may encounter degraded images. So, it is important to recover and enhance them using a dehazing process. Dehazing usually serves as a preprocessing step for low-, medium-, and high-level vision tasks. Therefore, this...
Article
Full-text available
In this paper, we proposed a novel generalized pixel value ordering–based reversible data hiding using firefly algorithm (GPVOFA). The sequence of minimum and maximum number pixels value has been used to embed the secret data while prediction and modification are held on minimum, and the maximum number of pixel blocks is used to embed the secret da...
Article
Artificial intelligence (AI) and computer vision (CV) methods become reliable to extract features from radiological images, aiding COVID-19 diagnosis ahead of the pathogenic tests and saving critical time for disease management and control. Thus, this review article focuses on cascading numerous deep learning-based COVID-19 computerized tomography...
Chapter
In order to compete in the KiTS21 challenge, we propose a 3D deep learning cascaded model for the renal enhanced CT image segmentation. The proposed model comprises two stages, where stage 1 segments the kidney and stage 2 segments the tumor and cyst. The proposed deep learning network architecture is based on the residual and 3D UNet architecture....
Chapter
Automated detection and segmentation of kidneys, tumors, and cysts are useful for renal diagnosis and treatment planning. Here we propose a two-stage contrast-enhanced CT detection and segmentation framework that automatically segments the kidney, kidney tumor, and cyst. Testing the proposed algorithm on the KiTS21 dataset, we achieve the mean dice...
Method
Full-text available
The kidney is an important organ of the human body and filters harmful substances from the blood. A kidney may cause some abnormalities. Among them, kidney stone (also called renal calculi, nephrolithiasis, or urolithiasis) is a highly prevalent disorder affecting approximately one in eleven people and is associated with multiple complications. To...
Article
Full-text available
Lung cancer has one of the highest mortality rates of all cancers and poses a severe threat to people’s health. Therefore, diagnosing lung nodules at an early stage is crucial to improving patient survival rates. Numerous computer-aided diagnosis (CAD) systems have been developed to detect and classify such nodules in their early stages. Currently,...
Article
Full-text available
Automated detection and segmentation of kidneys, tumors, and cysts are useful for renal diagnosis and treatment planning. Therefore, this article proposes a two-stage contrast-enhanced CT detection and segmentation framework that automatically segments the kidney, kidney tumor, and cyst. For this purpose, we use the KiTS21 dataset. Testing the prop...
Preprint
Full-text available
In order to compete in the KiTS21 challenge, we propose a 3D deep learning cascaded model for the renal enhanced CT image segmentation. The proposed model comprises two stages, where stage 1 segments the kidney and stage 2 segments the tumor and cyst. The proposed deep learning network architecture is based on the residual and 3D UNet architecture....
Article
Full-text available
This article presents a systematic overview of artificial intelligence (AI) and computer vision strategies for diagnosing the coronavirus disease of 2019 (COVID-19) using computerized tomography (CT) medical images. We analyzed the previous review works and found that all of them ignored classifying and categorizing COVID-19 literature based on com...
Article
Full-text available
Haze and fog had a great influence on the quality of images, and to eliminate this, dehazing and defogging are applied. For this purpose, an effective and automatic dehazing method is proposed. To dehaze a hazy image, we need to estimate two important parameters such as atmospheric light and transmission map. For atmospheric light estimation, the s...
Article
Full-text available
Given the broad applications of service-oriented architecture (SOA) in service-oriented software engineering, service-based systems (SBSs) built from existing Web services are becoming increasingly popular. As a result, the selection of the appropriate component services to include in SBSs has become a crucial step in the SBS-engineering process. U...
Article
Full-text available
In this paper, we proposed a new technique for reversible data hiding based on efficient compressed domain with multiple bit planes. We conducted a sequence of experiments to use block division scheme to appraise the result with different parameters and amended the probability of zero point in every block of histogram. This scheme attained more emb...
Article
Standards provide guidelines for the development of software and there are varieties of standards available in the market for software quality assurance. This paper is an assessment of the different standards of software quality assurance and mainly compares the inspection processes. Different steps are identified by different standards like IEEE a...

Questions

Questions (11)
Question
many image-processing applications, digital images must be zoomed to enlarge image details and highlight any small structures present. Need to know about the current advancement.
Question
I am working to estimate blur from blurred image, i am interested to know about the current advancement regarding mentioned area.
Question
What are the latest trends in Visual object tracking?
Question
What are the draw backs of blobs in image processing?
Question
Need some research articles using blocking mathcing techniques for thermal videos object tracking.
Question
how to put bounding box of a tracker in single object tracking?
Question
Hi. Please can you provide some more information about this project.It seems very interesting and offcourse will erit some more directions.Thanks
Question
Can you explain a little about your project?
Question
Need answer in the context of Object Tracking
Question
Object Tracking,Video Tracking,Video Surveillance,Image Processing,Machine Learning 

Network

Cited By