Muhammad Naeem Akram¹, Muhammad Usman Yaseen¹, Muhammad Waqar¹, Muhammad Imran^1,*, Aftab Hussain²

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3727-3744, 2023, DOI:10.32604/cmc.2023.041855

Abstract This study presents a deep learning model for efficient intracranial hemorrhage (ICH) detection and subtype classification on non-contrast head computed tomography (CT) images. ICH refers to bleeding in the skull, leading to the most critical life-threatening health condition requiring rapid and accurate diagnosis. It is classified as intra-axial hemorrhage (intraventricular, intraparenchymal) and extra-axial hemorrhage (subdural, epidural, subarachnoid) based on the bleeding location inside the skull. Many computer-aided diagnoses (CAD)-based schemes have been proposed for ICH detection and classification at both slice and scan levels. However, these approaches perform only binary classification and suffer from a large number of parameters, which… More >

Azhar Tursynova¹, Batyrkhan Omarov^1,2, Natalya Tukenova^3,*, Indira Salgozha⁴, Onergul Khaaval³, Rinat Ramazanov⁵, Bagdat Ospanov⁵

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1431-1446, 2023, DOI:10.32604/cmc.2023.034400

Abstract In the field of stroke imaging, deep learning (DL) has enormous untapped potential. When clinically significant symptoms of a cerebral stroke are detected, it is crucial to make an urgent diagnosis using available imaging techniques such as computed tomography (CT) scans. The purpose of this work is to classify brain CT images as normal, surviving ischemia or cerebral hemorrhage based on the convolutional neural network (CNN) model. In this study, we propose a computer-aided diagnostic system (CAD) for categorizing cerebral strokes using computed tomography images. Horizontal flip data magnification techniques were used to obtain more accurate categorization. Image Data Generator… More >

Maryam Wardah¹, Muhammad Mateen^1,*, Tauqeer Safdar Malik², Mohammad Eid Alzahrani³, Adil Fahad³, Abdulmohsen Almalawi⁴, Rizwan Ali Naqvi⁵

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2283-2299, 2023, DOI:10.32604/cmc.2023.030706

Abstract Brain hemorrhage is a serious and life-threatening condition. It can cause permanent and lifelong disability even when it is not fatal. The word hemorrhage denotes leakage of blood within the brain and this leakage of blood from capillaries causes stroke and adequate supply of oxygen to the brain is hindered. Modern imaging methods such as computed tomography (CT) and magnetic resonance imaging (MRI) are employed to get an idea regarding the extent of the damage. An early diagnosis and treatment can save lives and limit the adverse effects of a brain hemorrhage. In this case, a deep neural network (DNN)… More >

Roberta Costanzo¹, Vishal Parmar², Salvatore Marrone¹, Domenico Gerardo Iacopino¹, Giovanni Federico Nicoletti³, Giuseppe Emmanuele Umana⁴, Gianluca Scalia^3,*

Oncologie, Vol.24, No.4, pp. 937-942, 2022, DOI:10.32604/oncologie.2022.027155

Abstract Primary intracranial melanomas are rare, with a challenging diagnosis based only on clinical and imaging features. The authors described the case of an intracerebral right parieto-temporal melanoma mimicking a cavernoma in a patient affected by Crohn’s disease. A 67-year-old female patient with Crohn’s disease and small bowel stenosis was hospitalized for surgical removal of the terminal ileum and latero-lateral ileo-colic anastomosis. During postoperative week 1, the patient developed psychomotor agitation followed by altered consciousness. An urgent brain CT showed a right intracerebral parieto-temporal hemorrhage with intralesional calcifications. The patient underwent a decompressive craniectomy with hematoma drainage and a complete resection… More >

Ghassan Ahmed Ali¹, Thamer Mitib Ahmad Al Sariera^2,*, Muhammad Akram¹, Adel Sulaiman¹, Fekry Olayah¹

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1601-1616, 2023, DOI:10.32604/csse.2023.026119

Abstract Damage of the blood vessels in retina due to diabetes is called diabetic retinopathy (DR). Hemorrhages is the first clinically visible symptoms of DR. This paper presents a new technique to extract and classify the hemorrhages in fundus images. The normal objects such as blood vessels, fovea and optic disc inside retinal images are masked to distinguish them from hemorrhages. For masking blood vessels, thresholding that separates blood vessels and background intensity followed by a new filter to extract the border of vessels based on orientations of vessels are used. For masking optic disc, the image is divided into sub-images… More >

SUYING PU^1,#, HUI ZHENG^2,#, YUN TAO¹, JING SHAO¹, MINGNA YANG¹, SHUNJUN LI^1,*

BIOCELL, Vol.46, No.6, pp. 1545-1555, 2022, DOI:10.32604/biocell.2022.017544

Abstract Intracerebral hemorrhage (ICH) is the most serious type of stroke. High level of thrombin is found in the ICH. Ubiquitin-specific protease (USP) 31, a member of deubiquitinating enzymes family, has been found to negatively regulate the NF-κB pathway. However, the function of USP31 in ICH remains largely unknown. In the present study, the mRNA and protein expression levels of USP31 were measured by real-time PCR and western blot. Flow cytometry was used to measure cell apoptosis and the level of reactive oxygen species (ROS). In the current study, we found the mRNA level of USP31 was decreased in peripheral blood… More >

R. Shijitha^1,*, P. Karthigaikumar², A. Stanly Paul²

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5233-5249, 2022, DOI:10.32604/cmc.2022.020227

Abstract Brain Hemorrhagic stroke is a serious malady that is caused by the drop in blood flow through the brain and causes the brain to malfunction. Precise segmentation of brain hemorrhage is crucial, so an enhanced segmentation is carried out in this research work. The brain image of various patients has taken using an MRI scanner by the utilization of T1, T2, and FLAIR sequence. This work aims to segment the Brain Hemorrhagic stroke using deep learning-based Multi-resolution UNet (multires UNet) through morphological operations. It is hard to precisely segment the brain lesions to extract the existing region of stroke. This… More >

Osama S. Faragallah^1,*, Abdullah N. Muhammed², Taha S. Taha³, Gamal G. N. Geweid^4,5

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 215-225, 2021, DOI:10.32604/iasc.2021.019058

Abstract Medical image fusion is designed to help physicians in their decisions by providing them with a preclinical image with enough information. Accurate assessment and effective treatment of the disease reduce the time it takes to relieve the symptoms of the disease. This article utilizes an effective data fusion approach to work on two different imaging modalities; computed tomography (CT) and magnetic resonance imaging (MRI). The data fusion approach is based on the combination of singular value decomposition (SVD) and the Fast Discrete Curvelet Transform (FDCT) techniques to reduce processing time during the fusion process. The SVD-FDCT data fusion approach is… More >

D. Venugopal¹, T. Jayasankar², Mohamed Yacin Sikkandar³, Mohamed Ibrahim Waly³, Irina V. Pustokhina⁴, Denis A. Pustokhin⁵, K. Shankar^6,*

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2877-2893, 2021, DOI:10.32604/cmc.2021.015480

Abstract Data fusion is one of the challenging issues, the healthcare sector is facing in the recent years. Proper diagnosis from digital imagery and treatment are deemed to be the right solution. Intracerebral Haemorrhage (ICH), a condition characterized by injury of blood vessels in brain tissues, is one of the important reasons for stroke. Images generated by X-rays and Computed Tomography (CT) are widely used for estimating the size and location of hemorrhages. Radiologists use manual planimetry, a time-consuming process for segmenting CT scan images. Deep Learning (DL) is the most preferred method to increase the efficiency of diagnosing ICH. In… More >

Ali. E. Dabiri^1,2,*, Matthew Martin³, Ghassan S. Kassab¹

Molecular & Cellular Biomechanics, Vol.17, No.1, pp. 25-31, 2020, DOI:10.32604/mcb.2019.07310

Abstract The world-wide impact of traumatic injury and associated hemorrhage on human health and well-being is significant. Methods to manage bleeding from sites within the torso, referred to as non-compressible torso hemorrhage (NCTH), remain largely limited to the use of conventional operative techniques. The overall mortality rate of patients with NCTH is approximately 50%. Studies from the wars in Afghanistan and Iraq have suggested that up to 80% of potentially survivable patients die as a result of uncontrolled exsanguinating hemorrhage. The commercially available resuscitative endovascular balloon occlusion of the aorta (REBOA) is a percutaneous device for the rapid control of torso… More >