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  1. Due to the highly heterogeneity of the breast cancer, it would be desirable to obtain a non-invasive method to early predict the treatment response and survival outcome of the locally advanced breast cancer (L...

    Authors: Caifeng Wan, Liheng Zhou, Ye Jin, Fenghua Li, Lin Wang, Wenjin Yin, Yaohui Wang, Hongli Li, Lixin Jiang and Jinsong Lu
    Citation: BMC Medical Imaging 2023 23:216
  2. Retroperitoneal liposarcoma (RLPS) poses a challenging scenario for surgeons due to its unpredictable biological behavior. Surgery remains the primary curative option for RLPS; however, the need for additional...

    Authors: Dao-Ning Liu, Jian-Hui Wu, Zhong-Wu Li, Hai-Yue Wang, Xiu-Yun Tian and Chun-Yi Hao
    Citation: BMC Medical Imaging 2023 23:215
  3. This retrospective study aims to evaluate the diagnostic value of volume measurement of central pulmonary arteries using computer tomography pulmonary angiography (CTPA) for predicting pulmonary hypertension (...

    Authors: Wanwan Zhao, Jialing Guo, Ningli Dong, Huanhuan Hei, Xiaoyi Duan and Cong Shen
    Citation: BMC Medical Imaging 2023 23:211
  4. Mutated KRAS may indicate an invasive nature and predict prognosis in locally advanced rectal cancer (LARC). We aimed to establish a radiomic model using pretreatment T2W MRIs to predict KRAS status and explor...

    Authors: Yirong Xiang, Shuai Li, Maxiaowei Song, Hongzhi Wang, Ke Hu, Fengwei Wang, Zhi Wang, Zhiyong Niu, Jin Liu, Yong Cai, Yongheng Li, Xianggao Zhu, Jianhao Geng, Yangzi Zhang, Huajing Teng and Weihu Wang
    Citation: BMC Medical Imaging 2023 23:210
  5. The purpose of this study was to investigate the clinical utility of three-dimension (3D) high-resolution inversion recovery (IR)-prepared fast spoiled gradient-recalled (SPGR) magnetic resonance imaging (MRI)...

    Authors: Lulu Xuan, Jiafu Huang, Huikang Yin, Zehua Lu, Xiaoliang Yang, Liyue Yang and Chengjun Geng
    Citation: BMC Medical Imaging 2023 23:207
  6. 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...

    Authors: Haoming Zhuang, Aritrick Chatterjee, Xiaobing Fan, Shouliang Qi, Wei Qian and Dianning He
    Citation: BMC Medical Imaging 2023 23:205
  7. This study aims to investigate the potential of radiomics with multiple parameters from conventional T1 weighted imaging (T1WI) and susceptibility weighted imaging (SWI) in distinguishing between idiopathic Pa...

    Authors: Shuting Bu, Huize Pang, Xiaolu Li, Mengwan Zhao, Juzhou Wang, Yu Liu and Hongmei Yu
    Citation: BMC Medical Imaging 2023 23:204
  8. The role of threshold growth, as one of the major features (MFs) of hepatocellular carcinoma (HCC) in the Liver Imaging Reporting and Data System (LI-RADS) is inconsistent. This study evaluated the LI-RADS dia...

    Authors: Rong Lyu, Di Wang, Weijuan Hu, Zhongsong Gao, Changlu Yu, Jiao Wang, Mingge Li and Kefeng Jia
    Citation: BMC Medical Imaging 2023 23:201
  9. Deep learning has been used to detect or characterize prostate cancer (PCa) on medical images. The present study was designed to develop an integrated transfer learning nomogram (TLN) for the prediction of PCa...

    Authors: Junhao Chen, Bao Feng, Maoqing Hu, Feidong Huang, Yehang Chen, Xilun Ma and Wansheng Long
    Citation: BMC Medical Imaging 2023 23:200
  10. Chest radiography (CXR) is an adjunct tool in treatment planning and monitoring of the disease course of COVID-19 pneumonia. The purpose of the study was to describe the radiographic patterns and severity scor...

    Authors: Jumlong Saelim, Supika Kritsaneepaiboon, Vorawan Charoonratana and Puttichart Khantee
    Citation: BMC Medical Imaging 2023 23:199
  11. Maxillary morphology has long been a subject of interest due to its possible impact on palatally and labially displaced canines. This study aims to conduct a comparison of the palate morphology between individ...

    Authors: Farshad Sobhani, Amirfarhang Miresmaeili, Hossein Mahjub and Maryam Farhadian
    Citation: BMC Medical Imaging 2023 23:198
  12. In recent years, there has been a growing trend towards utilizing Artificial Intelligence (AI) and machine learning techniques in medical imaging, including for the purpose of automating quality assurance. In ...

    Authors: Tarraf Torfeh, Souha Aouadi, SA Yoganathan, Satheesh Paloor, Rabih Hammoud and Noora Al-Hammadi
    Citation: BMC Medical Imaging 2023 23:197
  13. The purpose of this study is to investigate the use of radiomics and deep features obtained from multiparametric magnetic resonance imaging (mpMRI) for grading prostate cancer. We propose a novel approach call...

    Authors: Hasan Khanfari, Saeed Mehranfar, Mohsen Cheki, Mahmoud Mohammadi Sadr, Samir Moniri, Sahel Heydarheydari and Seyed Masoud Rezaeijo
    Citation: BMC Medical Imaging 2023 23:195
  14. To evaluate the repeatability and agreement of Fourier-domain optical coherence tomography (AOCT-1000 M and RTVue XR) and partial coherence interferometry biometer (IOL Master 500) in measuring corneal thickne...

    Authors: Hailong Ni, Suzhong Xu, Li Tian, Jieli Mao, Jing Li, Na Lin, Peike Hu, Zhiyi Wu, Xiang Chen, Zhishu Bao, Jingwei Zheng, Peihua Yan and Ruzhi Deng
    Citation: BMC Medical Imaging 2023 23:194
  15. 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography (18F-FDG PET) could help evaluate metabolic abnormalities by semi-quantitative measurement to identify autoimmune encephalitis (AE). Few studies hav...

    Authors: Lili Liu, Zhehao Lyu, Huimin Li, Lin Bai, Yong Wan and Ping Li
    Citation: BMC Medical Imaging 2023 23:193
  16. There are no specific magnetic resonance imaging (MRI) features that distinguish pilocytic astrocytoma (PA) from adamantinomatous craniopharyngioma (ACP). In this study we compared the frequency of a novel enh...

    Authors: Shumin Xu, Wanqun Yang, Yi Luo, Xiaoyu Wang, Yaowen Li, Xianlei Meng, Yuze Zhang, Hongwu Zeng and Biao Huang
    Citation: BMC Medical Imaging 2023 23:191
  17. This study aimed to compare the diagnostic efficiency of Ovarian-Adnexal Reporting and Data System (O-RADS) and doctors’ subjective judgment in diagnosing the malignancy risk of adnexal masses.

    Authors: Shan Zhou, Yuyang Guo, Lieming Wen, Jieyu Liu, Yaqian Fu, Fang Xu, Minghui Liu and Baihua Zhao
    Citation: BMC Medical Imaging 2023 23:190
  18. Although it is generally thought that disturbance of perfusion in the anterior lobe of the pituitary gland leads to complete or partial hypopituitarism, the gadolinium (Gd) enhancement findings on Magnetic Res...

    Authors: Mariko Doai, Yuka Nishino, Yasuhiko Hayashi, Masatsune Ito and Munetaka Matoba
    Citation: BMC Medical Imaging 2023 23:188
  19. Kidney volume is important in the management of renal diseases. Unfortunately, the currently available, semi-automated kidney volume determination is time-consuming and prone to errors. Recent advances in its ...

    Authors: Lukas Müller, Dativa Tibyampansha, Peter Mildenberger, Torsten Panholzer, Florian Jungmann and Moritz C. Halfmann
    Citation: BMC Medical Imaging 2023 23:187
  20. Renal cell carcinoma (RCC) is a heterogeneous group of cancers. The collagen fiber content in the tumor microenvironment of renal cancer has an important role in tumor progression and prognosis. A radiomics mo...

    Authors: Zhongyuan Li, Ning Wang, Xue Bing, Yuhan Li, Jian Yao, Ruobing Li and Aimei Ouyang
    Citation: BMC Medical Imaging 2023 23:186
  21. 1H magnetic resonance spectroscopy (1H-MRS) can be used to study neurological disorders because it can be utilized to examine the concentrations of related metabolites. However, the diagnostic utility of differen...

    Authors: Biao Qu, Hejuan Tan, Min Xiao, Dongbao Liu, Shijin Wang, Yiwen Zhang, Runhan Chen, Gaofeng Zheng, Yonggui Yang, Gen Yan and Xiaobo Qu
    Citation: BMC Medical Imaging 2023 23:185
  22. To explore the value of magnetic resonance angiography (MRA) and high resolution magnetic resonance vessel wall imaging (HRMR-VWI) in cervicocranial artery dissection (CCAD) for the disease diagnosis, course s...

    Authors: Weiqiong Ma, Kexin Zhou, Bowen Lan, Kangyin Chen, Wuming Li and Guihua Jiang
    Citation: BMC Medical Imaging 2023 23:184
  23. There is a lack of understanding of the mechanisms by which the CNS is injured in multiple sclerosis (MS). Since Theiler’s murine encephalomyelitis virus (TMEV) infection in SJL/J mice is an established model ...

    Authors: Michael Linzey, Krista DiSano, Nora Welsh, James C. Ford, Francesca Gilli, Heather Wishart and Andrew Pachner
    Citation: BMC Medical Imaging 2023 23:183
  24. The value of radiomics features from the adrenal gland and periadrenal fat CT images for predicting disease progression in patients with COVID-19 has not been studied extensively. We assess the value of radiom...

    Authors: Mudan Zhang, Xuntao Yin, Wuchao Li, Yan Zha, Xianchun Zeng, Xiaoyong Zhang, Jingjing Cui, Zhong Xue, Rongpin Wang and Chen Liu
    Citation: BMC Medical Imaging 2023 23:181
  25. To provide normative data and to determine accuracy and reliability of preoperative measurements of spondylolisthesis and kyphosis on supine static magnetic resonance imaging (MRI) of patients with degenerativ...

    Authors: Eddie de Dios, Mats Laesser, Isabella M. Björkman-Burtscher, Lars Lindhagen and Anna MacDowall
    Citation: BMC Medical Imaging 2023 23:180
  26. Pulmonary nodule growth rate assessment is critical in the management of subsolid pulmonary nodules (SSNs) during clinical follow-up. The present study aimed to develop a model to predict the growth rate of SSNs.

    Authors: Zong Jing Ma, Zhuang Xuan Ma, Ying Li Sun, De Chun Li, Liang Jin, Pan Gao, Cheng Li and Ming Li
    Citation: BMC Medical Imaging 2023 23:177
  27. We focused on Differentiated pseudoprogression (PPN) of progression (PN) and the response to radiotherapy (RT) or chemoradiotherapy (CRT) using diffusion and metabolic imaging.

    Authors: Maryam Zamanian, Iraj Abedi, Fatemeh Danazadeh, Alireza Amouheidari and Bentolhoda Otroshi Shahreza
    Citation: BMC Medical Imaging 2023 23:176
  28. UTE has been used to depict lung parenchyma. However, the insufficient discussion of its performance in pediatric pneumonia compared with conventional sequences is a gap in the existing literature. The objecti...

    Authors: Yan Sun, Yujie Chen, Xuesheng Li, Yi Liao, Xijian Chen, Yu Song, Xinyue Liang, Yongming Dai, Dapeng Chen and Gang Ning
    Citation: BMC Medical Imaging 2023 23:175
  29. With the rise in importance of personalized medicine and deep learning, we combine the two to create personalized neural networks. The aim of the study is to show a proof of concept that data from just one pat...

    Authors: Christian Strack, Kelsey L. Pomykala, Heinz-Peter Schlemmer, Jan Egger and Jens Kleesiek
    Citation: BMC Medical Imaging 2023 23:174
  30. To investigate the prognosis value of a combined model based on 18F-fluoro-deoxyglucose positron emission tomography-computed tomography (18F-FDG PET-CT) baseline and interim parameters in patients with diffuse l...

    Authors: Jun Dang, Xiaojuan Peng, Ping Wu, Yutang Yao, Xiaofei Tan, Zhenyan Ye, Xuemei Jiang, Xiao Jiang, Yongli Liu, Shirong Chen and Zhuzhong Cheng
    Citation: BMC Medical Imaging 2023 23:173
  31. Automatic segmentation of brain tumors by deep learning algorithm is one of the research hotspots in the field of medical image segmentation. An improved FPN network for brain tumor segmentation is proposed to...

    Authors: Haitao Sun, Shuai Yang, Lijuan Chen, Pingyan Liao, Xiangping Liu, Ying Liu and Ning Wang
    Citation: BMC Medical Imaging 2023 23:172
  32. A super-resolution deep learning reconstruction (SR-DLR) algorithm trained using data acquired on the ultrahigh spatial resolution computed tomography (UHRCT) has the potential to provide better image quality ...

    Authors: Makoto Orii, Misato Sone, Takeshi Osaki, Yuta Ueyama, Takuya Chiba, Tadashi Sasaki and Kunihiro Yoshioka
    Citation: BMC Medical Imaging 2023 23:171
  33. This study sought to evaluate the worth of the general characteristics of enhanced CT images and the histogram parameters of each stage in distinguishing pleomorphic adenoma (PA) and adenolymphoma (AL).

    Authors: Feifei Xia, Foqing Guo, Zhe Liu, Jie Zeng, Xuehua Ma, Chongqing Yu and Changxue Li
    Citation: BMC Medical Imaging 2023 23:169
  34. To explore the value of multiparametric MRI markers for preoperative prediction of Ki-67 expression among patients with rectal cancer.

    Authors: Xiuzhen Yao, Weiqun Ao, Xiandi Zhu, Shuyuan Tian, Xiaoyu Han, Jinwen Hu, Wenjie Xu, Guoqun Mao and Shuitang Deng
    Citation: BMC Medical Imaging 2023 23:168

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