Mir Tanvir Islam, Shafin T. Mashfu, Abrar Faisal, Sadman Chowdhury Siam et al.
Glaucoma is an irreversible neurodegenerative disease, where intraocular hypertension is developed due to the increased aqueous humor and blockage of the drainage system between the iris and cornea. As a result, the optic nerve head, which sends visual stimulus from our eyes to the brain, is damaged...
Nilanjan Dey, V. Rajinikanth, Simon Fong, M. Shamim Kaiser et al.
The coronavirus disease (COVID-19) caused by a novel coronavirus, SARS-CoV-2, has been declared a global pandemic. Due to its infection rate and severity, it has emerged as one of the major global threats of the current generation. To support the current combat against the disease, this research aim...
Yasmin M. Kassim, Kannappan Palaniappan, Feng Yang, Mahdieh Poostchi et al.
Computer-assisted algorithms have become a mainstay of biomedical applications to improve accuracy and reproducibility of repetitive tasks like manual segmentation and annotation. We propose a novel pipeline for red blood cell detection and counting in thin blood smear microscopy images, named RBCNe...
Nagaraja Gundluru, Dharmendra Singh Rajput, Kuruva Lakshmanna, Rajesh Kaluri et al.
In today's world, diabetic retinopathy is a very severe health issue, which is affecting many humans of different age groups. Due to the high levels of blood sugar, the minuscule blood vessels in the retina may get damaged in no time and further may lead to retinal detachment and even sometimes lead...
Mohaimenul Azam Khan Raiaan, Kaniz Fatema, Inam Ullah Khan, Sami Azam et al.
Diabetic retinopathy (DR) is a common complication of diabetes mellitus, and retinal blood vessel damage can lead to vision loss and blindness if not recognized at an early stage. Manual DR detection using large fundus image data is time-consuming and error-prone. An effective automatic DR detection...
Md. Zabirul Islam, Md. Milon Islam, Amanullah Asraf
Abstract Nowadays automatic disease detection has become a crucial issue in medical science with the rapid growth of population. Coronavirus (COVID-19) has become one of the most severe and acute diseases in very recent times that has been spread globally. Automatic disease detection framework assis...
Pramit Dutta, Khaleda Akther Sathi, Md. Azad Hossain, M. Ali Akber Dewan
The current advancement towards retinal disease detection mainly focused on distinct feature extraction using either a convolutional neural network (CNN) or a transformer-based end-to-end deep learning (DL) model. The individual end-to-end DL models are capable of only processing texture or shape-ba...
Iftekharul Abedeen, Md Ashiqur Rahman, Fatema Zohra Prottyasha, Tasnim Ahmed et al.
Digital radiography is one of the most common and cost-effective standards for the diagnosis of bone fractures. For such diagnoses expert intervention is required which is time-consuming and demands rigorous training. With the recent growth of computer vision algorithms, there is a surge of interest...
Mohammad Monirul Islam, Xin Yao, Shahriar Nirjon, Md. Ariful Islam et al.
In this paper, we propose two cooperative ensemble learning algorithms, i.e., NegBagg and NegBoost, for designing neural network (NN) ensembles. The proposed algorithms incrementally train different individual NNs in an ensemble using the negative correlation learning algorithm. Bagging and boosting...
Md. Mahfuz Ahmed, Md. Maruf Hossain, Md. Rakibul Islam, Md Shahin Ali et al.
Brain tumor, a leading cause of uncontrolled cell growth in the central nervous system, presents substantial challenges in medical diagnosis and treatment. Early and accurate detection is essential for effective intervention. This study aims to enhance the detection and classification of brain tumor...
Saikat Islam Khan, Ashef Shahrior, Md. Razaul Karim, Mahmodul Hasan et al.
Breast cancer diagnosis from biopsy tissue images conducted manually by pathologists is costly, time-consuming, and disagreements among specialists. Nowadays, the advancement of the Computer-Aided Diagnosis (CAD) system allows pathologists to identify breast cancer more reliably and quickly.For this...
Md. Tariqul Islam, Sheikh Asif Imran, Asiful Arefeen, Mahmudul Hasan et al.
Of late, usage of neural network in the field of disease detection has been on advanced stage. Hence, ocular disease diagnosis has also been under the influence of machine learning. Human eye is very prone to disorders like cataract, glaucoma, myopia etc. and with the passage of time, these diseases...
Md. Sarwar Kamal, Nilanjan Dey, Linkon Chowdhury, Syed Irtija Hasan et al.
Glaucoma causes irreversible blindness. In 2020, about 80 million people worldwide had glaucoma. Existing machine learning (ML) models are limited to glaucoma prediction, where clinicians, patients, and medical experts are unaware of how data analysis and decision-making are handled. Explainable art...
Subrato Bharati, Prajoy Podder, M. Rubaiyat Hossain Mondal, V. B. Surya Prasath
This paper focuses on the application of deep learning (DL) based model in the analysis of novel coronavirus disease (COVID-19) from X-ray images. The novelty of this work is in the development of a new DL algorithm termed as optimized residual network (CO-ResNet) for COVID-19. The proposed CO-ResNe...
Md. Nahiduzzaman, Md. Robiul Islam, S. M. Riazul Islam, Md. Omaer Faruq Goni et al.
This paper exploits the extreme learning machine (ELM) approach to address diabetic retinopathy (DR), a medical condition in which impairment occurs to the retina caused by diabetes. DR, a leading cause of blindness worldwide, is a sort of swelling leakage due to excessive blood sugar in the retina ...