Precise segmentation techniques in various medical images

M Harouni, M Karimi, S Rafieipour - Artificial Intelligence and …, 2021 - taylorfrancis.com
Today numerous imaging systems are utilized in medical treatment. There are a variety of
imaging techniques for the diagnosis of brain tumors, lung nodules and liver tumors and …

Survey on segmentation of liver from CT images

S Priyadarsini, D Selvathi - 2012 IEEE international conference …, 2012 - ieeexplore.ieee.org
Liver cancer is one of the most popular cancer diseases and causes a large amount of death
every year. The chances for liver cancer in men and women have increased to 40% and …

Semi-automatic liver tumor segmentation with adaptive region growing and graph cuts

Z Yang, Y Zhao, M Liao, S Di, Y Zeng - Biomedical signal processing and …, 2021 - Elsevier
Segmenting liver tumors from computed tomography (CT) images plays a very important role
in computer-aided diagnosis, surgical planning, and treatment monitoring. However …

Focal dice loss-based V-Net for liver segments classification

B Prencipe, N Altini, GD Cascarano, A Brunetti… - Applied Sciences, 2022 - mdpi.com
Liver segmentation is a crucial step in surgical planning from computed tomography scans.
The possibility to obtain a precise delineation of the liver boundaries with the exploitation of …

A residual-learning-based multi-scale parallel-convolutions-assisted efficient CAD system for liver tumor detection

M Maqsood, M Bukhari, Z Ali, S Gillani, I Mehmood… - Mathematics, 2021 - mdpi.com
Smart multimedia-based medical analytics and decision-making systems are of prime
importance in the healthcare sector. Liver cancer is commonly stated to be the sixth most …

Semi-automated segmentation of single and multiple tumors in liver CT images using entropy-based fuzzy region growing

A Baâzaoui, W Barhoumi, A Ahmed, E Zagrouba - IRBM, 2017 - Elsevier
Aims The liver CT image segmentation is still until now a challenging problem due to the
fuzzy nature of the tumor transition to the surrounding tissues. The objective of this article is …

Recent survey on medical image segmentation

MAM Salem, A Atef, A Salah, M Shams - Handbook of Research on …, 2017 - igi-global.com
This chapter presents a survey on the techniques of medical image segmentation. Image
segmentation methods are given in three groups based on image features used by the …

A computer-aided diagnostic system for liver tumor detection using modified U-Net architecture

A Kalsoom, M Maqsood, S Yasmin, M Bukhari… - The Journal of …, 2022 - Springer
A multimedia-based medical decision-making system is an ultimate requirement in the
medical imaging domain. In the healthcare sector, achieving quick and efficient results is …

[PDF][PDF] Comparison of segmentation tools for multiple modalities in medical imaging

S Bhadoria, P Aggarwal… - Journal of advances in …, 2012 - pdfs.semanticscholar.org
Image segmentation plays a crucial role in many medical imaging applications by extracting
the regions of interest. Accurate segmentation of medical images is a key step in the use of …

Chest X-ray segmentation using Sauvola thresholding and Gaussian derivatives responses

M Kiran, I Ahmed, N Khan, AG Reddy - Journal of Ambient Intelligence …, 2019 - Springer
This paper presents a simple, flexible and an effective lung segmentation technique called
ST-GD (Sauvola thresholding-Gaussian derivatives) method. In this technique Sauvola …