[HTML][HTML] The liver tumor segmentation benchmark (lits)

P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen… - Medical Image …, 2023 - Elsevier
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark
(LiTS), which was organized in conjunction with the IEEE International Symposium on …

Deep learning techniques in liver tumour diagnosis using CT and MR imaging-A systematic review

B Lakshmipriya, B Pottakkat, G Ramkumar - Artificial Intelligence in …, 2023 - Elsevier
Deep learning has become a thriving force in the computer aided diagnosis of liver cancer,
as it solves extremely complicated challenges with high accuracy over time and facilitates …

Comparison and evaluation of methods for liver segmentation from CT datasets

T Heimann, B Van Ginneken, MA Styner… - IEEE transactions on …, 2009 - ieeexplore.ieee.org
This paper presents a comparison study between 10 automatic and six interactive methods
for liver segmentation from contrast-enhanced CT images. It is based on results from the …

Automated abdominal multi-organ segmentation with subject-specific atlas generation

R Wolz, C Chu, K Misawa, M Fujiwara… - IEEE transactions on …, 2013 - ieeexplore.ieee.org
A robust automated segmentation of abdominal organs can be crucial for computer aided
diagnosis and laparoscopic surgery assistance. Many existing methods are specialized to …

[KİTAP][B] Guide to medical image analysis

KD Toennies - 2017 - Springer
The methodology presented in the first edition was considered established practice or
settled science in the medical image analysis community in 2010–2011. Progress in this …

Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography

M Moghbel, S Mashohor, R Mahmud… - Artificial Intelligence …, 2018 - Springer
Computed tomography (CT) imaging remains the most utilized modality for liver-related
cancer screening and treatment monitoring purposes. Liver, liver tumor and liver vasculature …

[KİTAP][B] Visual computing for medicine: theory, algorithms, and applications

B Preim, CP Botha - 2013 - books.google.com
Visual Computing for Medicine, Second Edition, offers cutting-edge visualization techniques
and their applications in medical diagnosis, education, and treatment. The book includes …

[HTML][HTML] Discriminative dictionary learning for abdominal multi-organ segmentation

T Tong, R Wolz, Z Wang, Q Gao, K Misawa… - Medical image …, 2015 - Elsevier
An automated segmentation method is presented for multi-organ segmentation in abdominal
CT images. Dictionary learning and sparse coding techniques are used in the proposed …

[PDF][PDF] Shape constrained automatic segmentation of the liver based on a heuristic intensity model

D Kainmüller, T Lange, H Lamecker - … 3D Segmentation in the Clinic: A …, 2007 - Citeseer
We present a fully automatic 3D segmentation method for the liver from contrast-enhanced
CT data. It is based on a combination of a constrained free-form and statistical deformable …

Fully automatic liver and tumor segmentation from CT image using an AIM-Unet

F Özcan, ON Uçan, S Karaçam, D Tunçman - Bioengineering, 2023 - mdpi.com
The segmentation of the liver is a difficult process due to the changes in shape, border, and
density that occur in each section in computed tomography (CT) images. In this study, the …