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Article
Open AccessLearning and depicting lobe-based radiomics feature for COPD Severity staging in low-dose CT images
Chronic obstructive pulmonary disease (COPD) is a prevalent and debilitating respiratory condition that imposes a significant healthcare burden worldwide. Accurate staging of COPD severity is crucial for patie...
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Article
NL-CS Net: Deep Learning with Non-local Prior for Image Compressive Sensing
Deep learning has been applied to compressive sensing (CS) of images successfully in recent years. However, existing network-based methods are often trained as the black box, in which the lack of prior knowled...
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Article
Neuroimage analysis using artificial intelligence approaches: a systematic review
In the contemporary era, artificial intelligence (AI) has undergone a transformative evolution, exerting a profound influence on neuroimaging data analysis. This development has significantly elevated our comp...
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Article
Open AccessNew insight in massive cerebral infarction predictions after anterior circulation occlusion
To predict massive cerebral infarction (MCI) occurrence after anterior circulation occlusion (ACO) by cASPECTS-CTA-CS (combined ASPECTS and CTA-CS). Of 185 cerebral infarction patients with the ACO, their coll...
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Article
Open AccessA radiomics based method for prediction of prostate cancer Gleason score using enlarged region of interest
Prostate cancer (PCa) is one of the most common cancers in men worldwide, and its timely diagnosis and treatment are becoming increasingly important. MRI is in increasing use to diagnose cancer and to distingu...
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Article
Depicting and predicting changes of lung after lobectomy for cancer by using CT images
Lobectomy is an effective and well-established therapy for localized lung cancer. This study aimed to assess the lung and lobe change after lobectomy and predict the postoperative lung volume. The study includ...
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Article
Open AccessNomograms integrating CT radiomic and deep learning signatures to predict overall survival and progression-free survival in NSCLC patients treated with chemotherapy
This study aims to establish nomograms to accurately predict the overall survival (OS) and progression-free survival (PFS) in patients with non-small cell lung cancer (NSCLC) who received chemotherapy alone as...
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Article
Transformer-based 3D U-Net for pulmonary vessel segmentation and artery-vein separation from CT images
Transformer-based methods have led to the revolutionizing of multiple computer vision tasks. Inspired by this, we propose a transformer-based network with a channel-enhanced attention module to explore context...
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Article
TSP-UDANet: two-stage progressive unsupervised domain adaptation network for automated cross-modality cardiac segmentation
Accurate segmentation of cardiac anatomy is a prerequisite for the diagnosis of cardiovascular disease. However, due to differences in imaging modalities and imaging devices, known as domain shift, the segment...
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Article
Abnormal functional connectivity density involvement in freezing of gait and its application for subty** Parkinson’s disease
The pathophysiological mechanisms at work in Parkinson’s disease (PD) patients with freezing of gait (FOG) remain poorly understood. Functional connectivity density (FCD) could provide an unbiased way to analy...
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Article
Open AccessUsing CT radiomic features based on machine learning models to subtype adrenal adenoma
Functioning and non-functioning adrenocortical adenoma are two subtypes of benign adrenal adenoma, and their differential diagnosis is crucial. Current diagnostic procedures use an invasive method, adrenal ven...
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Article
Open AccessDeep multiple instance learning for predicting chemotherapy response in non-small cell lung cancer using pretreatment CT images
The individual prognosis of chemotherapy is quite different in non-small cell lung cancer (NSCLC). There is an urgent need to precisely predict and assess the treatment response. To develop a deep multiple-ins...
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Article
A comprehensive survey on deep learning techniques in CT image quality improvement
High-quality computed tomography (CT) images are key to clinical diagnosis. However, the current quality of an image is limited by reconstruction algorithms and other factors and still needs to be improved. Wh...
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Article
Open AccessAlterations of functional connectivity of the lateral habenula in subclinical depression and major depressive disorder
Major depressive disorder (MDD) is a common cause of disability and morbidity, affecting about 10% of the population worldwide. Subclinical depression (SD) can be understood as a precursor of MDD, and therefor...
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Chapter and Conference Paper
Breast Tumor Segmentation in Ultrasound Images Based on U-NET Model
Breast cancer is the second leading cause of cancer death among women in the United States. If detected and diagnosed in the early stages, it increases survival rates and lowers treatment costs. Emerging deep ...
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Article
Open AccessAltered spontaneous neural activity in the precuneus, middle and superior frontal gyri, and hippocampus in college students with subclinical depression
Subclinical depression (ScD) is a prevalent condition associated with relatively mild depressive states, and it poses a high risk of develo** into major depressive disorder (MDD). However, the neural patholo...
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Article
A review for cervical histopathology image analysis using machine vision approaches
Because cervical histopathology image analysis plays a very importation role in the cancer diagnosis and medical treatment processes, since the 1980s, more and more effective machine vision techniques are intr...
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Article
Predicting Unnecessary Nodule Biopsies from a Small, Unbalanced, and Pathologically Proven Dataset by Transfer Learning
This study explores an automatic diagnosis method to predict unnecessary nodule biopsy from a small, unbalanced, and pathologically proven database. The automatic diagnosis method is based on a convolutional n...
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Chapter and Conference Paper
A SARS-CoV-2 Microscopic Image Dataset with Ground Truth Images and Visual Features
SARS-CoV-2 has characteristics of wide contagion and quick propagation velocity. To analyse the visual information of it, we build a SARS-CoV-2 Microscopic Image Dataset (SC2-MID) with 48 electron microscopic ...
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Article
Correction to: Non-contrast MRI for breast screening: preliminary study on detectability of benign and malignant lesions in women with dense breasts
In the original version of the article, the image of Figure 2 was erroneously duplicated as Figure 4. The correct version of Figure 4 is given below. The original article has been corrected.
