4.6 Article

Segmentation of lung cancer-caused metastatic lesions in bone scan images using self-defined model with deep supervision

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Multidisciplinary Sciences

Deep learning based automated diagnosis of bone metastases with SPECT thoracic bone images

Qiang Lin et al.

Summary: This paper presents deep classifiers based on deep networks for reliably classifying SPECT bone images in automated diagnosis of metastasis. The classifiers, including VGG, ResNet and DenseNet, perform well in identifying bone metastasis with SPECT imaging, achieving high accuracy, precision, recall, specificity, F-1 score and AUC.

SCIENTIFIC REPORTS (2021)

Article Radiology, Nuclear Medicine & Medical Imaging

Object-oriented classification approach for bone metastasis mapping from whole-body bone scintigraphy

Mihaela Antonina Calin et al.

Summary: The study introduced a fast object-oriented classification method for bone scintigraphy images, which showed promising results in detecting bone metastases with an overall accuracy of 86%-87%. The use of k-nearest-neighbor and support vector machine classifiers proved to be effective in improving diagnostic accuracy for bone metastases.

PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS (2021)

Article Computer Science, Information Systems

Bone Metastasis Detection in the Chest and Pelvis from a Whole-Body Bone Scan Using Deep Learning and a Small Dataset

Da-Chuan Cheng et al.

Summary: This study aimed to establish an early diagnostic system for bone metastasis of prostate cancer using a deep convolutional neural network, which showed satisfactory performance on a small dataset. Hard example mining can be used to improve the system's sensitivity and precision, providing a potential pre-diagnostic report for physicians.

ELECTRONICS (2021)

Article Medicine, General & Internal

Lesion-Based Bone Metastasis Detection in Chest Bone Scintigraphy Images of Prostate Cancer Patients Using Pre-Train, Negative Mining, and Deep Learning

Da-Chuan Cheng et al.

Summary: This study aimed to explore efficient ways to diagnose bone metastasis early using bone scintigraphy images through negative mining, pre-training, the convolutional neural network, and deep learning. The developed system showed high sensitivity and precision in detecting and classifying bone metastasis locations in chest X-ray images.

DIAGNOSTICS (2021)

Article Engineering, Biomedical

Seizures classification based on higher order statistics and deep neural network

Rahul Sharma et al.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2020)

Article Engineering, Biomedical

Automated emotion recognition based on higher order statistics and deep learning algorithm

Rahul Sharma et al.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2020)

Article Chemistry, Multidisciplinary

A Deep-Learning Approach for Diagnosis of Metastatic Breast Cancer in Bones from Whole-Body Scans

Nikolaos Papandrianos et al.

APPLIED SCIENCES-BASEL (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Development of Convolutional Neural Networks to identify bone metastasis for prostate cancer patients in bone scintigraphy

Nikolaos Papandrianos et al.

ANNALS OF NUCLEAR MEDICINE (2020)

Review Computer Science, Artificial Intelligence

Classifying functional nuclear images with convolutional neural networks: a survey

Qiang Lin et al.

IET IMAGE PROCESSING (2020)

Article Computer Science, Artificial Intelligence

Automated diagnosis of bone metastasis based on multi-view bone scans using attention-augmented deep neural networks

Yong Pi et al.

MEDICAL IMAGE ANALYSIS (2020)

Article Computer Science, Information Systems

MaligNet: Semisupervised Learning for Bone Lesion Instance Segmentation Using Bone Scintigraphy

Terapap Apiparakoon et al.

IEEE ACCESS (2020)

Article Computer Science, Information Systems

Class Balanced Loss for Image Classification

Lin Wang et al.

IEEE ACCESS (2020)

Article Computer Science, Artificial Intelligence

Clustering-based natural image denoising using dictionary learning approach in wavelet domain

Asem Khmag et al.

SOFT COMPUTING (2019)

Article Engineering, Biomedical

Moving object tracking in clinical scenarios: application to cardiac surgery and cerebral aneurysm clipping

Sarada Prasad Dakua et al.

INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

Computer-aided detection of bone metastasis in bone scintigraphy images using parallelepiped classification method

Florina-Gianina Elfarra et al.

ANNALS OF NUCLEAR MEDICINE (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

Family of boundary overlap metrics for the evaluation of medical image segmentation

Varduhi Yeghiazaryan et al.

JOURNAL OF MEDICAL IMAGING (2018)

Article Radiology, Nuclear Medicine & Medical Imaging

Automatic lung segmentation in functional SPECT images using active shape models trained on reference lung shapes from CT

Grigorios-Aris Cheimariotis et al.

ANNALS OF NUCLEAR MEDICINE (2018)

Article Engineering, Electrical & Electronic

Towards Left Ventricle Segmentation From Magnetic Resonance Images

Sarada Prasad Dakua

IEEE SENSORS JOURNAL (2017)

Article Oncology

CADBOSS: A computer-aided diagnosis system for whole-body bone scintigraphy scans

Ali Aslantas Emre Dandil et al.

JOURNAL OF CANCER RESEARCH AND THERAPEUTICS (2016)

Article Computer Science, Artificial Intelligence

LV Segmentation Using Stochastic Resonance and Evolutionary Cellular Automata

Sarada Prasad Dakua

INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE (2015)

Article Mathematical & Computational Biology

Design of Natural Image Denoising Filter Based on Second-Generation Wavelet Transformation and Principle Component Analysis

Asem Khmag et al.

JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS (2015)

Article Computer Science, Interdisciplinary Applications

Lung Segmentation in Chest Radiographs Using Anatomical Atlases With Nonrigid Registration

Sema Candemir et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2014)

Article Computer Science, Interdisciplinary Applications

Automatic Tuberculosis Screening Using Chest Radiographs

Stefan Jaeger et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2014)

Article Engineering, Electrical & Electronic

Detection of Left Ventricular Myocardial Contours from Ischemic Cardiac MR Images

Sarada Prasad Dakua et al.

IETE JOURNAL OF RESEARCH (2011)

Article Cardiac & Cardiovascular Systems

Automatic Left Ventricular Contour Extraction from Cardiac Magnetic Resonance Images Using Cantilever Beam and Random Walk Approach

Sarada Prasad Dakua et al.

CARDIOVASCULAR ENGINEERING (2010)

Article Radiology, Nuclear Medicine & Medical Imaging

Computer-Assisted Interpretation of Planar Whole-Body Bone Scans

May Sadik et al.

JOURNAL OF NUCLEAR MEDICINE (2008)

Article Radiology, Nuclear Medicine & Medical Imaging

A new computer-based decision-support system for the interpretation of bone scans

May Sadik et al.

NUCLEAR MEDICINE COMMUNICATIONS (2006)