Systematic review of computing approaches for breast cancer detection based computer aided diagnosis using mammogram images

DA Zebari, DA Ibrahim, DQ Zeebaree… - Applied Artificial …, 2021 - Taylor & Francis
Breast cancer is one of the most prevalent types of cancer that plagues females. Mortality
from breast cancer could be reduced by diagnosing and identifying it at an early stage. To …

A review of segmentation algorithms applied to B-mode breast ultrasound images: A characterization approach

Kriti, J Virmani, R Agarwal - Archives of Computational Methods in …, 2021 - Springer
Ultrasound imaging modality is used prominently for breast cancer screening and diagnosis
because of its safety, portability, ease of use and low cost. Over the years, computer-assisted …

Assessment of despeckle filtering algorithms for segmentation of breast tumours from ultrasound images

J Virmani, R Agarwal - Biocybernetics and Biomedical Engineering, 2019 - Elsevier
In the present work, the performance assessment of despeckle filtering algorithms has been
carried out for (a) noise reduction in breast ultrasound images and (b) segmentation of …

Real‐time automated segmentation of breast lesions using CNN‐based deep learning paradigm: Investigation on mammogram and ultrasound

K Atrey, BK Singh, A Roy… - International Journal of …, 2022 - Wiley Online Library
The existing studies involving single imaging modalities (ie, mammogram (MG) or
ultrasound (US)) to detect breast lesions have demonstrated limited clinical application …

Deep learning for detecting dilated or contracted pupils

FC Rodrigues, DBP Quintanilha, AC de Paiva… - … Signal Processing and …, 2024 - Elsevier
Pupilometry is the precise measurement of pupil diameter, widely employed in medical
contexts to assess this ocular structure's dilation and constriction reactions. These …

AGSAM: Agent-Guided Segment Anything Model for Automatic Segmentation in Few-Shot Scenarios

H Zhou, Y He, X Cui, Z Xie - Bioengineering, 2024 - mdpi.com
Precise medical image segmentation of regions of interest (ROIs) is crucial for accurate
disease diagnosis and progression assessment. However, acquiring high-quality annotated …

Neutrosophic and fuzzy C-means clustering for breast ultrasound image segmentation

HA Nugroho, M Rahmawaty, Y Triyani… - 2017 9th International …, 2017 - ieeexplore.ieee.org
Breast ultrasound image segmentation is one of the most difficult tasks due to its speckle
noise, poor quality and location of the breast nodule. In this research, we propose …

Malignant Detection of Breast Nodules On BIRADS-Based Ultrasound Images Margin, Orientation, And Posterior

Y Triyani, W Khabzli, W Styorini - Journal of Electronics, Electromedical …, 2023 - jeeemi.org
Breast cancer has the largest prevalence in the world in 2020, with 2,261,419 cases or
11.7%. It is also the leading cause of cancer death, accounting for 6.9% of all cancer deaths …

Breast cancer detection and validation using dual modality imaging

K Atrey, BK Singh, A Roy… - 2020 First International …, 2020 - ieeexplore.ieee.org
Early detection of malignancy is important in order to reduce morbidity and mortality rate.
However, existing approaches are based on a single modality having limited performance …

Texture analysis and classification in ultrasound medical images for determining echo pattern characteristics

HA Nugroho, M Rahmawaty, Y Triyani… - 2017 7th IEEE …, 2017 - ieeexplore.ieee.org
Ultrasound is one of the imaging modalities commonly used for detecting mass
abnormalities of nodule. The observation of ultrasound images is conducted by the …