Armughan Ali^1,2, Hooria Shahbaz², Robertas Damaševičius^3,*

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1367-1398, 2025, DOI:10.32604/cmc.2025.059301 - 26 March 2025

Abstract Skin cancer is the most prevalent cancer globally, primarily due to extensive exposure to Ultraviolet (UV) radiation. Early identification of skin cancer enhances the likelihood of effective treatment, as delays may lead to severe tumor advancement. This study proposes a novel hybrid deep learning strategy to address the complex issue of skin cancer diagnosis, with an architecture that integrates a Vision Transformer, a bespoke convolutional neural network (CNN), and an Xception module. They were evaluated using two benchmark datasets, HAM10000 and Skin Cancer ISIC. On the HAM10000, the model achieves a precision of 95.46%, an… More >

Kun Liu¹, Chen Bao^1,*, Sidong Liu²

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4451-4468, 2025, DOI:10.32604/cmc.2024.059053 - 06 March 2025

Abstract Large amounts of labeled data are usually needed for training deep neural networks in medical image studies, particularly in medical image classification. However, in the field of semi-supervised medical image analysis, labeled data is very scarce due to patient privacy concerns. For researchers, obtaining high-quality labeled images is exceedingly challenging because it involves manual annotation and clinical understanding. In addition, skin datasets are highly suitable for medical image classification studies due to the inter-class relationships and the inter-class similarities of skin lesions. In this paper, we propose a model called Coalition Sample Relation Consistency (CSRC),… More >

Shiren Ye, Qi Meng, Shuo Zhang, Hui Wang^*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2415-2429, 2025, DOI:10.32604/cmc.2024.058250 - 17 February 2025

Abstract WCE (Wireless Capsule Endoscopy) is a new technology that combines computer vision and medicine, allowing doctors to visualize the conditions inside the intestines, achieving good diagnostic results. However, due to the complex intestinal environment and limited pixel resolution of WCE videos, lesions are not easily detectable, and it takes an experienced doctor 1–2 h to analyze a complete WCE video. The use of computer-aided diagnostic methods, assisting or even replacing manual WCE diagnosis, has significant application value. In response to the issue of intestinal lesion detection in WCE videos, this paper proposes a multi-scale feature… More >

Khadija Manzoor¹, Fiaz Majeed², Ansar Siddique², Talha Meraj³, Hafiz Tayyab Rauf^4,*, Mohammed A. El-Meligy⁵, Mohamed Sharaf⁶, Abd Elatty E.Abd Elgawad⁶

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1459-1459, 2025, DOI:10.32604/cmc.2024.061588 - 03 January 2025

Abstract This article has no abstract. More >

Grace Helene Wegrzyn¹, Melissa Kilianek², Suzanne Iwaz³, Patricia Vidal¹, Ryan W. Dobbs¹

Canadian Journal of Urology, Vol.31, No.1, pp. 11809-11812, 2024

Abstract Mullerianosis is a rare, complex, benign tumor most commonly found in the bladder and often mistaken for a neoplastic lesion. Herein, we report a case of mullerianosis in a 65-year-old woman who presented with an incidental 2 cm bladder mass found on cross-sectional imaging. A mixed cystic and solid tumor was identified on cystoscopy and a transurethral resection of the suspected tumor was performed with histopathology confirming a final diagnosis of mullerianosis. While an unusual diagnosis, mullerianosis of the urinary bladder needs to be correctly identified to provide appropriate treatment and avoid misdiagnosis. More >

VIRGINIA LOTTI¹, GAETANO DE SIENA², STEFANO BACCI^3,*

BIOCELL, Vol.48, No.12, pp. 1751-1759, 2024, DOI:10.32604/biocell.2024.057904 - 30 December 2024

Abstract Background: Impaired wound healing is one of the most well-known complications of type 2 diabetes mellitus. Experimental evidence suggested that treatment with Exendin-4, a glucagon-like peptide-1 agonist displaying a wide range of antidiabetic effects, can promote tissue regeneration. Objectives: Thus, this study aimed to examine the efficacy of topical treatment with Exendin-4 in accelerating wound healing in normoglycemic and hyperglycemic mice. Methods: For this purpose, two wounds inflicted on the back skin of 12 normo- and 12 hyperglycemic mice were injected intradermally with either saline solution or Exendin-4. Wounds were collected at the time of abrasion… More >

Rafid Sagban^1,2,*, Haydar Abdulameer Marhoon^3,4, Saadaldeen Rashid Ahmed^5,6,*

Intelligent Automation & Soft Computing, Vol.39, No.6, pp. 1035-1051, 2024, DOI:10.32604/iasc.2024.058416 - 30 December 2024

Abstract Skin cancer is a highly frequent kind of cancer. Early identification of a phenomenon significantly improves outcomes and mitigates the risk of fatalities. Melanoma, basal, and squamous cell carcinomas are well-recognized cutaneous malignancies. Malignant We can differentiate Melanoma from non-pigmented carcinomas like basal and squamous cell carcinoma. The research on developing automated skin cancer detection systems has primarily focused on pigmented malignant type melanoma. The limited availability of datasets with a wide range of lesion categories has hindered in-depth exploration of non-pigmented malignant skin lesions. The present study investigates the feasibility of automated methods for… More >

Rabia Javed¹, Tanzila Saba², Tahani Jaser Alahmadi^3,*, Sarah Al-Otaibi⁴, Bayan AlGhofaily², Amjad Rehman²

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 809-825, 2024, DOI:10.32604/cmc.2024.052755 - 15 October 2024

Abstract Cancer poses a significant threat due to its aggressive nature, potential for widespread metastasis, and inherent heterogeneity, which often leads to resistance to chemotherapy. Lung cancer ranks among the most prevalent forms of cancer worldwide, affecting individuals of all genders. Timely and accurate lung cancer detection is critical for improving cancer patients’ treatment outcomes and survival rates. Screening examinations for lung cancer detection, however, frequently fall short of detecting small polyps and cancers. To address these limitations, computer-aided techniques for lung cancer detection prove to be invaluable resources for both healthcare practitioners and patients alike.… More >

Yang Hua^#, Jinyu Sun^#, Yuxuan Lou, Hao Zhang, Jing Shi^*, Wei Sun^*

Congenital Heart Disease, Vol.19, No.3, pp. 279-291, 2024, DOI:10.32604/chd.2024.051190 - 26 July 2024

Abstract Background: White matter lesion (WML) is common in aging brain and is associated with cognitive impairment and dementia. However, recent studies reported an association between patent foramen ovale (PFO) and WML in migraineurs, especially in young, middle-aged migraineurs. Our retrospective, case-control study aims to describe the clinical characteristics of WML in this population and to explore potential risk factors. Methods: 226 patients with migraine and PFO were consecutively initially screened. Relevant factors were selected by the least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression model. A Nomogram was employed to visualize… More >

K. Umapathi^1,*, S. Shobana¹, Anand Nayyar², Judith Justin³, R. Vanithamani³, Miguel Villagómez Galindo⁴, Mushtaq Ahmad Ansari⁵, Hitesh Panchal^6,*

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1875-1901, 2024, DOI:10.32604/cmc.2024.047961 - 15 May 2024

Abstract Breast cancer detection heavily relies on medical imaging, particularly ultrasound, for early diagnosis and effective treatment. This research addresses the challenges associated with computer-aided diagnosis (CAD) of breast cancer from ultrasound images. The primary challenge is accurately distinguishing between malignant and benign tumors, complicated by factors such as speckle noise, variable image quality, and the need for precise segmentation and classification. The main objective of the research paper is to develop an advanced methodology for breast ultrasound image classification, focusing on speckle noise reduction, precise segmentation, feature extraction, and machine learning-based classification. A unique approach… More >