Mahmoud Ragab^1,2,3,*, Alaa F. Nahhas⁴

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2849-2864, 2022, DOI:10.32604/cmc.2022.028855

Abstract Earlier recognition of breast cancer is crucial to decrease the severity and optimize the survival rate. One of the commonly utilized imaging modalities for breast cancer is histopathological images. Since manual inspection of histopathological images is a challenging task, automated tools using deep learning (DL) and artificial intelligence (AI) approaches need to be designed. The latest advances of DL models help in accomplishing maximum image classification performance in several application areas. In this view, this study develops a Deep Transfer Learning with Rider Optimization Algorithm for Histopathological Classification of Breast Cancer (DTLRO-HCBC) technique. The proposed DTLRO-HCBC technique aims to categorize… More >

D. Banumathy^1,*, Osamah Ibrahim Khalaf², Carlos Andrés Tavera Romero³, P. Vishnu Raja⁴, Dilip Kumar Sharma⁵

Computer Systems Science and Engineering, Vol.44, No.1, pp. 595-612, 2023, DOI:10.32604/csse.2023.025611

Abstract The most salient argument that needs to be addressed universally is Early Breast Cancer Detection (EBCD), which helps people live longer lives. The Computer-Aided Detection (CADs)/Computer-Aided Diagnosis (CADx) system is indeed a software automation tool developed to assist the health professions in Breast Cancer Detection and Diagnosis (BCDD) and minimise mortality by the use of medical histopathological image classification in much less time. This paper purposes of examining the accuracy of the Convolutional Neural Network (CNN), which can be used to perceive breast malignancies for initial breast cancer detection to determine which strategy is efficient for the early identification of… More >

Ali G. Alkhathami^*

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 235-247, 2022, DOI:10.32604/iasc.2022.024952

Abstract Breast cancer is one of the main causes of death in women. When body tissues start behaves abnormally and the ratio of tissues growth becomes asymmetrical then this stage is called cancer. Invasive ductal carcinoma (IDC) is the early stage of breast cancer. The early detection and diagnosis of invasive ductal carcinoma is a significant step for the cure of IDC breast cancer. This paper presents a convolutional neural network (CNN) approach to detect and visualize the IDC tissues in breast on histological images dataset. The dataset consists of 90 thousand histopathological images containing two categories: Invasive Ductal Carcinoma positive… More >

CINZIA SIGNORINI^*, GIULIA COLLODEL, ELENA MORETTI

BIOCELL, Vol.46, No.4, pp. 881-884, 2022, DOI:10.32604/biocell.2022.018062

Abstract The manuscript deals with our studies and experiences in the assessment of cytoskeleton in different cellular models and situations. The immunofluorescent study of several cytoskeletal proteins was relevant in the evaluation of a therapy for osteoarthritis, in case of alkaptonuria and in testing the efficacy of docetaxel in neuroblastoma cancer cells leading to apoptosis. A relevant part of our experience focus on the study of cytoskeleton in seminiferous epithelium and spermatozoa, identifying alterations affecting blood-testis barrier after a silver nanoparticle treatment, chromosomal segregation in case of varicocele, sperm motility and diagnosing systematic sperm defects as “Primary ciliary dyskinesia” and “Dysplasia… More >

Schahrazad Soltane^*, Sameer Alsharif , Salwa M.Serag Eldin

Computer Systems Science and Engineering, Vol.40, No.2, pp. 629-644, 2022, DOI:10.32604/csse.2022.019333

Abstract Current cancer diagnosis procedure requires expert knowledge and is time-consuming, which raises the need to build an accurate diagnosis support system for lymphoma identification and classification. Many studies have shown promising results using Machine Learning and, recently, Deep Learning to detect malignancy in cancer cells. However, the diversity and complexity of the morphological structure of lymphoma make it a challenging classification problem. In literature, many attempts were made to classify up to four simple types of lymphoma. This paper presents an approach using a reliable model capable of diagnosing seven different categories of rare and aggressive lymphoma. These Lymphoma types… More >

Imran Ahmed^1,*, Humaira Sardar¹, Hanan Aljuaid², Fakhri Alam Khan¹, Muhammad Nawaz¹, Adnan Awais¹

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3365-3381, 2021, DOI:10.32604/cmc.2021.018486

Abstract Osteosarcoma is one of the most widespread causes of bone cancer globally and has a high mortality rate. Early diagnosis may increase the chances of treatment and survival however the process is time-consuming (reliability and complexity involved to extract the hand-crafted features) and largely depends on pathologists’ experience. Convolutional Neural Network (CNN—an end-to-end model) is known to be an alternative to overcome the aforesaid problems. Therefore, this work proposes a compact CNN architecture that has been rigorously explored on a Small Osteosarcoma histology Image Dataaseet (a high-class imbalanced dataset). Though, during training, class-imbalanced data can negatively affect the performance of… More >

TING LAN, SHENG QIN, XIAOJIN GONG, PING ZHENG, JIAXIN YAN, YANG LIU^*

BIOCELL, Vol.45, No.5, pp. 1313-1319, 2021, DOI:10.32604/biocell.2021.015923

Abstract Invasive stratified mucin-producing carcinoma (ISMC) is a recently described histologic variant of high-risk human papillomavirus (HPV)-associated endocervical adenocarcinoma, as the putative invasive counterpart of the stratified mucin-producing intraepithelial lesion (SMILE). ISMC can display variable architectural patterns and usually coexists with other more conventional types of HPV-associated carcinomas, which makes diagnosis and differential diagnosis of ISMC is difficult for pathologists. Moreover, the prognosis of ISMC is still controversial. We analyzed 6 ISMCs with detailed pathological and clinical information. Intraepithelial lesion, including 1 high-grade squamous intraepithelial lesion and 1 SMILE, was found. Various architectures were observed (including nest, glandular, solid, trabecular, and… More >

Yongtao Yu, Guangdong Zou^*

Oncologie, Vol.23, No.2, pp. 293-301, 2021, DOI:10.32604/Oncologie.2021.015520

Abstract Objective: The purpose was to explore the value of multi-slice spiral CT (MSCT) multiplanar reconstruction technique in the diagnosis and clinicopathological analysis of gastrointestinal lymphoma (GIL). Methods: 82 GIL patients treated in our hospital from February 2018 to February 2019 were selected as the experimental group of this study, and 82 patients with other gastrointestinal tumors diagnosed by pathology during the same period were selected as the control group. Both groups of patients were scanned by MSCT and analyzed by multiplanar reconstruction technique to compare the diagnostic results and clinicopathological indexes of the two groups. Results: The diagnostic accuracy of… More >

T. Jayasree^1,*, S.Emerald Shia²

Sound & Vibration, Vol.55, No.2, pp. 141-161, 2021, DOI:10.32604/sv.2021.011734

Abstract This paper presents the pathological voice detection and classification techniques using signal processing based methodologies and Feed Forward Neural Networks (FFNN). The important pathological voices such as Autism Spectrum Disorder (ASD) and Down Syndrome (DS) are considered for analysis. These pathological voices are known to manifest in different ways in the speech of children and adults. Therefore, it is possible to discriminate ASD and DS children from normal ones using the acoustic features extracted from the speech of these subjects. The important attributes hidden in the pathological voices are extracted by applying different signal processing techniques. In this work, three… More >

Sophie Gardrat^*, Vincent Cockenpot

Oncologie, Vol.22, No.4, pp. 195-202, 2020, DOI:10.32604/oncologie.2020.013698

Abstract The pathological examination of ocular tumors has specificities in terms of macroscopic management, microscopic analysis, and molecular examinations requiring special attention. We discuss here the difficulties encountered in the reception in the pathological anatomy laboratory of conjunctival samples, enucleation and orbital exenteration pieces, then detail the diagnostic and theranostic, microscopic and molecular characteristics of ocular tumor pathologies. Conjunctival tumors (epithelial, melanocytic and lymphoid), choroidal tumors (including uveal melanoma) and retinoblastoma are treated. Because of their low frequency and their features, these tumors should be the subject of anatomo-clinical discussions.

Résumé:
L’examen anatomopathologique des tumeurs oculaires comporte des spécificités en termes… More >