Machine learning in ultrasound computer‐aided diagnostic systems: a survey

Q Huang, F Zhang, X Li - BioMed research international, 2018 - Wiley Online Library
The ultrasound imaging is one of the most common schemes to detect diseases in the
clinical practice. There are many advantages of ultrasound imaging such as safety …

Image segmentation techniques: statistical, comprehensive, semi-automated analysis and an application perspective analysis of mathematical expressions

Sakshi, V Kukreja - Archives of Computational Methods in Engineering, 2023 - Springer
Segmentation has been a rooted area of research having diverse dimensions. The roots of
image segmentation and its associated techniques have supported computer vision, pattern …

An improved YOLOv3 algorithm to detect molting in swimming crabs against a complex background

C Tang, G Zhang, H Hu, P Wei, Z Duan, Y Qian - Aquacultural Engineering, 2020 - Elsevier
Traditional methods of breeding soft-shell crabs mainly rely on manual identification, which
has high costs regarding manpower and resources. Manual inspection may also interfere …

Computer aided breast cancer detection using ultrasound images

S Pavithra, R Vanithamani, J Justin - Materials Today: Proceedings, 2020 - Elsevier
Breast cancer is the second prevalent type of cancer among women. Breast Ultrasound
(BUS) imaging is one of the most frequently used diagnostic tools to detect and classify …

A novel technique for detecting crop diseases with efficient feature extraction

S Desai, R Kanphade, R Priyadarshi… - IETE Journal of …, 2023 - Taylor & Francis
Classification and feature extraction are other planned areas of study, since they build upon
the basis of computer picture processing technology and have a direct impact on the results …

Computer aided diagnostic system for ultrasound liver images: A systematic review

MY Jabarulla, HN Lee - Optik, 2017 - Elsevier
In this article an in-depth overview is presented on Computer aided diagnostic (CAD)
system's usage for liver cancer. Besides, in a broader sense highlighting the technical …

Particle swarm optimisation K-means clustering segmentation of foetus ultrasound image

D Parasar, VR Rathod - International Journal of Signal and …, 2017 - inderscienceonline.com
The purpose of medical image segmentation is to extract information such as volume,
shape, motion of organs for detecting abnormalities from the medical image for improvement …

Optimization of fuzzy c-means (FCM) clustering in cytology image segmentation using the gray wolf algorithm

M Mohammdian-Khoshnoud, AR Soltanian… - BMC Molecular and Cell …, 2022 - Springer
Background Image segmentation is considered an important step in image processing.
Fuzzy c-means clustering is one of the common methods of image segmentation. However …

[PDF][PDF] 计算机辅助诊断技术在超声医学中的应用进展

毕珂, 王茵 - 肿瘤影像学, 2019 - zhongliuyingxiangxue.com
计算机辅助诊断(computer aided diagnosis, CAD) 在超声医学中的应用已有多年历史, 在乳腺,
甲状腺, 颈动脉和肝脏等领域已有较好的应用成果. 近年来, 随着深度学习的提出 …

[PDF][PDF] Non-linear separation of classes using a kernel based fuzzy c-means (KFCM) approach

AP Byju - 2015 - essay.utwente.nl
Fuzzy classification of remote sensing image allows the characterization and classification of
land covers with improved robustness and accuracy. Coarser resolution images contain …