Comprehensive Review on MRI-Based Brain Tumor Segmentation: A Comparative Study from 2017 Onwards

A Verma, SN Shivhare, SP Singh, N Kumar… - … Methods in Engineering, 2024 - Springer
Brain tumor segmentation has been a challenging and popular research problem in the area
of medical imaging and computer-aided diagnosis. In the last few years, especially since …

A Novel Neural Network for Joint Lesion Segmentation and Confidence Score Generation from PET Image

M Daraee, E Saeedzadeh… - 2022 IEEE Nuclear …, 2022 - ieeexplore.ieee.org
Lesions segmentation from PET images is considered very high challenging task compared
to the anatomical organ delineation regarding irregular and/or unpredictable …

Segmentation of brain tumor MRI images using watershed thresholding

ATA Atiyah - 2023 - openaccess.altinbas.edu.tr
The detection of brain tumors using magnetic resonance imaging (MRI) brain scans has
become one of the most active areas of research in the field of medical image processing …

Topology-based Cost Function: a Novel Approach for Organ Delineation in Medical Images with Deep Learning Methods

R Karimzadeh, E Fatemizadeh… - 2022 IEEE Nuclear …, 2022 - ieeexplore.ieee.org
Medical images segmentation plays a crucial role in diagnosis and treatment planning.
Manual segmentation is a tedious and time-consuming task for experts and prone to human …

Joint Region of Interest Detection and Bone Age Estimation from Radiograph of the Hand

F Maleki, A Karimian, SS Ashrafi… - 2022 IEEE Nuclear …, 2022 - ieeexplore.ieee.org
Skeletal bone age assessment is a conventional clinical method used to determine
adolescent maturity in orthodontics, kinematics, pediatrics, forensic science, and other …

Role of Neural Network Architectures and Loss Functions in Semantic Segmentation of Medical Images

FG Inchehbroun, A Nodehi, A Ehsanirad… - 2022 IEEE Nuclear …, 2022 - ieeexplore.ieee.org
Regarding the vast application of deep learning solutions for different tasks, the selection of
the appropriate architectural and loss function is critical to achieving the desired results …

A Novel Context Loss Function Defined on the Feature Maps: Evaluation for Lesion Segmentation from PET Images versus Conventional Loss Functions

M Daraee, E Saeedzadeh… - 2022 IEEE Nuclear …, 2022 - ieeexplore.ieee.org
Lesion segmentation from PET images is highly challenging due to the lack of a
definite/predictable shape/morphology for the lesions compared to the anatomical organ …

Automated Pulmonary Nodules Detection from CT Images using Hierarchical YOLO v5s and 3D Convolutional Neural Network Classifier

YA Razlighi, A Kamali-Asl, H Arabi… - 2022 IEEE Nuclear …, 2022 - ieeexplore.ieee.org
Lung cancer is one of the leading causes of death worldwide. Early detection of lung cancer
would enable physicians to treat patients properly and noticeably reduce death rates. In this …

A Dedicated Neural Network for Automated Segmentation of Prostate Gland from PET Images

Z Shirkhani, A Kamali-Asl, R Jahangir… - 2022 IEEE Nuclear …, 2022 - ieeexplore.ieee.org
In PET imaging, prostate segmentation would provide useful quantitative information
regarding the radiotracer absorption for radiomics studies with the aim of identifying the …

A Novel Attention-based Neural Network for Automated Lung Lesion Delineation from 4DCT Images

P Talebi, E Saeedzadeh… - 2022 IEEE Nuclear …, 2022 - ieeexplore.ieee.org
Radiotherapy plays an important role in the treatment of non-small cell lung cancer.
Accurate segmentation of the gross target volume (GTV) is critical for successful …