Current Medical Imaging Reviews最新文献

{"title":"Application of Artificial Intelligence (AI) System in Opportunistic Screening and Diagnostic Population in a Middle-income Nation.","authors":"Marlina Tanty Ramli Hamid, Nazimah Ab Mumin, Shamsiah Abdul Hamid, Kartini Rahmat","doi":"10.2174/0115734056280191231207052903","DOIUrl":"https://doi.org/10.2174/0115734056280191231207052903","url":null,"abstract":"<p><strong>Objective: </strong>This study evaluates the effectiveness of artificial intelligence (AI) in mammography in a diverse population from a middle-income nation and compares it to traditional methods.</p><p><strong>Methods: </strong>A retrospective study was conducted on 543 mammograms of 467 Malays, 48 Chinese, and 28 Indians in a middle-income nation. Three breast radiologists interpreted the examinations independently in two reading sessions (with and without AI support). Breast density and BI-RADS categories were assessed, comparing the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) results.</p><p><strong>Results: </strong>Of 543 mammograms, 69.2% had lesions detected. Biopsies were performed on 25%(n=136), with 66(48.5%) benign and 70(51.5%) malignant. Substantial agreement in density assessment between the radiologist and AI software (κ =0.606, p < 0.001) and the BI-RADS category with and without AI (κ =0.74, p < 0.001). The performance of the AI software was comparable to the traditional methods. The sensitivity, specificity, PPV, and NPV or radiologists alone, radiologist + AI, and AI alone were 81.9%,90.4%,56.0%, and 97.1%; 81.0%, 93.1%,55.5%, and 97.0%; and 90.0%,76.5%,36.2%, and 98.1%, respectively. AI software enhances the accuracy of lesion diagnosis and reduces unnecessary biopsies, particularly for BI-RADS 4 lesions. The AI software results for synthetic were almost similar to the original 2D mammography, with AUC of 0.925 and 0.871, respectively.</p><p><strong>Conclusion: </strong>AI software may assist in the accurate diagnosis of breast lesions, enhancing the efficiency of breast lesion diagnosis in a mixed population of opportunistic screening and diagnostic patients.</p><p><strong>Key messages: </strong>• The use of artificial intelligence (AI) in mammography for population-based breast cancer screening has been validated in high-income nations, with reported improved diagnostic performance. Our study evaluated the usage of an AI tool in an opportunistic screening setting in a multi-ethnic and middle-income nation. • The application of AI in mammography enhances diagnostic accuracy, potentially leading to reduced unnecessary biopsies. • AI integration into the workflow did not disrupt the performance of trained breast radiologists, as there is a substantial inter-reader agreement for BI-RADS category assessment and breast density.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139984486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Withdrawn: Percutaneous Multi-angle Thread Needle for Two- or Three-part Unstable Fractures of the Proximal Humerus in Older Population","authors":"Changcheng Liu","doi":"10.2174/0115734056259280231227114253","DOIUrl":"10.2174/0115734056259280231227114253","url":null,"abstract":"<p><p>Since the authors are not responding to the editor’s request to fulfill the editorial requirement, the article has been\u0000withdrawn.</p><p><p>Bentham Science apologizes to the readers of the journal for any inconvenience this may have caused.</p><p><p>The Bentham editorial policy on article withdrawal can be found at https://benthamscience.com/journal/33/editorialpolicy</p><p><strong>Bentham science disclaimer: </strong>It is a condition of publication that manuscripts submitted to this journal have not been published and will not be simultaneously submitted or published elsewhere. Furthermore, any data, illustration, structure, or table that has been published elsewhere must be reported, and copyright permission for reproduction must be obtained. Plagiarism is strictly forbidden, and by submitting the article for publication, the authors agree that the publishers\u0000have the legal right to take appropriate action against the authors if plagiarism or fabricated information is discovered. By submitting a manuscript, the authors agree that the copyright of their article is transferred to the publishers if and when the article is accepted for publication.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139984488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hepatic Pecoma versus Hepatocellular Carcinoma In The Noncirrhotic Liver on Gd-EOB-DTPA-Enhanced MRI: A Diagnostic Challenge.","authors":"Ruixia Ma, Shi-Ting Feng, Xiaoqi Zhou, Meichen Chen, Jifei Wang, Zhi Dong","doi":"10.2174/0115734056269369231213102554","DOIUrl":"https://doi.org/10.2174/0115734056269369231213102554","url":null,"abstract":"<p><strong>Aim: </strong>Hepatic perivascular epithelioid cell tumors (PEComa) often mimic hepatocellular carcinoma (HCC) in patients without cirrhosis. This study aimed to develop a nomogram using imaging characteristics on Gd-EOB-DTPA-enhanced MRI and to distinguish PEComa from HCC in a noncirrhotic liver.</p><p><strong>Methods: </strong>Forty patients with non-cirrhotic Gd-EOB-DTPA-enhanced magnetic resonance imaging(MRI) were included in our study. A multivariate logistic regression model was used to select significant variables to distinguish PEComa from HCC. A nomogram was developed based on the regression model. The performance of the nomogram was assessed with respect to the ROC curve and calibration curve. Decision curve analysis (DCA) was performed to evaluate the clinical usefulness of the nomogram.</p><p><strong>Results: </strong>Two significant predictors were identified: the appearance of an early draining vein and the T1D value of tumors. The ROC curve showed that the area under the curve (AUC) of the model to predict the risk of PEComa was 0.91 (95% CI: 0.80~1) and showed that the model had high specificity (92.3%) and sensitivity (88.9%). The nomogram incorporating these two predictors showed favorable calibration, which was validated using 1000 resampling procedures, and the corrected C-index of this model was 0.90. Furthermore, DCA analysis showed that the model had clinical practicability.</p><p><strong>Conclusion: </strong>In conclusion, the nomogram model showed favorable predictive accuracy for distinguishing PEComa from HCC in non-cirrhotic patients and may aid in clinical decision-making.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139984446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microwave Imaging: Locating Bone Fractures using Patch Antenna of ISM Band.","authors":"Joselin Jeya Sheela J, Gul Shaira Banu Jahangeer, N Duraichi, M Logeshwaran, B Jeyapoornima","doi":"10.2174/0115734056282184240112095915","DOIUrl":"https://doi.org/10.2174/0115734056282184240112095915","url":null,"abstract":"<p><strong>Background: </strong>The human skeletal system relies heavily on the integrity of bones, which provide structural support and safeguard vital organs. Accurate detection is paramount for effective diagnosis. Conventional methods for identifying fractures manually are not only time-consuming but also susceptible to errors.</p><p><strong>Methods: </strong>The proposed methodology hinges on a patch antenna operating at 2.4 GHz and a bone phantom housing a simulated fracture, where the antenna is scanned. The collected signals are then processed with Delay-and-Sum (DAS), and Delay-Multiply-and-Sum (DMAS) reconstruction algorithms. The resulting images offer visual insights into the location of fractures.</p><p><strong>Results: </strong>Through experimentation, the efficacy of the images varies considerably in terms of their capacity for noise and artifact suppression. While DAS exhibits reasonable effectiveness, it suppresses noise and artifacts comprehensively. In contrast, DMAS offers clearer and more precise images of bone fractures.</p><p><strong>Conclusion: </strong>In summary, the research introduces a cost-effective and non-invasive strategy for detecting bone fractures. By involving a patch antenna at 2.4 GHz, along with image reconstruction algorithms like DMAS and DAS, one can effectively visualize the location of bone fractures. The experimental results highlight the superiority of DMAS over DAS in terms of contrast resolution, making it a highly promising avenue for fracture detection.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139984460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multimodal Imaging for the Diagnosis of Massive Left Atrial Metastasis from Lung Cancer - A Case Report.","authors":"Li Sun, Ronghong Jiao, Yuanyuan Xing, Yuquan Ye","doi":"10.2174/0115734056272579240110051837","DOIUrl":"https://doi.org/10.2174/0115734056272579240110051837","url":null,"abstract":"<p><strong>Background: </strong>Secondary cardiac tumors are a rare disease that is hard to detect when the tumor is small and asymptomatic. This case report focuses on a massive pulmonary metastasis filling almost the entire left atrium. Multimodal enhancement imaging, cardiac contrast-enhanced ultrasound (CEUS), enhanced electron computed tomography, and positron emission tomography imaging were applied to detect the malignant origin of this case. The aim of this project was to provide an important basis for clinical treatment and decision-making with multimodal imaging.</p><p><strong>Case presentation: </strong>The patient was hospitalized with suspected to be a lumbar spine fracture. According to the multimodal imaging, pathologically confirmed to suffer a cardiac metastasis from small cell lung cancer. EP-regimen (Etoposide 0.1gd 1-5+Nedaplatin 30mgd 1-4) was selected for the systemic chemotherapy of the patient. During three years of follow-up, the left intra-atrial occupancy was significantly reduced.</p><p><strong>Conclusion: </strong>Multimodality imaging can cover up the deficiencies of single imaging examinations and further clarify and enrich the understanding of the relationship between the location and the surrounding structure of the mass, thus providing a good reference for clinical treatment and decisionmaking.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139984466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does Postlong Coronavirus 2019 Disease Affect Renal Stiffness without any Chronic Systemic Disorders?","authors":"Serdal Çitil, Yusuf Aksu","doi":"10.2174/0115734056258544231115103528","DOIUrl":"https://doi.org/10.2174/0115734056258544231115103528","url":null,"abstract":"<p><strong>Background: </strong>In the last few years, coronavirus disease 2019 (COVID-19) has changed human lifestyle, behavior, and perception of life. This disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). In the literature, there are limited studies about the late renal effects of COVID-19 that reflect the systemic involvement of this disease.</p><p><strong>Aim: </strong>In the present study, we aimed to compare sonoelastographic changes in both kidneys between patients who had totally recovered from COVID-19 and healthy individuals using strain wave elastography (SWE).</p><p><strong>Methods: </strong>This study was conducted between June 2021 and May 2022 in Kahramanmaraş City Hospital Department of Radiology. File and archive records were retrospectively evaluated. Basic demographic, laboratory, and renal ultrasonography (USG) and sonoelastographic findings were screened and noted. Two groups were defined to compare sonoelastographic findings. Post-long COVID-19 group had 92 post-long COVID-19 patients, and the comparator group had 9 healthy individuals\". Both groups' demographic, laboratory, and ultrasound-elastographic findings were assessed.</p><p><strong>Results: </strong>The post-long COVID-19 group had a higher renal elastographic value than the comparator group (1.52 [0.77-2.3] vs. 0.96 [0.54-1.54], p<0.001). There were no statistically significant differences between the two groups in terms of age (p=0.063), gender (p=0.654), or body mass index (BMI) (p=0.725), however, there was a significant difference observed between the two groups in the renal strain ratio (RSR). According to an ROC analysis, an RSR cutoff of >1.66 predicted post-long COVID-19 with 44.9% sensitivity and 81.9% specificity. (AUC=0.655, p<0.001). A separate ROC analysis was performed to predict post-long COVID-19 with a BMI cutoff of <33.52, kg/m2 sensitivity of 92.4% and specificity of 17% (AUC=0.655, p<0.001).</p><p><strong>Conclusion: </strong>We demonstrated that renal parenchymal stiffness increases with SWE in post-long COVID-19 patients.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139984441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Application of MRI in Coronavirus Disease 2019: A Bibliometric Analysis.","authors":"Jinqun Hu, Jian Xiong, Jing Jiang, Ying Wei, Fayang Ling, Shichun Luo, Jiao Chen, Chengguo Su, Xiao Wang, Wenchuan Qi, Fanrong Liang","doi":"10.2174/0115734056274864231227071026","DOIUrl":"https://doi.org/10.2174/0115734056274864231227071026","url":null,"abstract":"<p><strong>Background: </strong>Currently, coronavirus disease 2019 (COVID-19) continues to remain in the pandemic stage, leading to severe challenges in the global public healthcare system. Magnetic resonance imaging (MRI) methods have played an important role in the diagnosis of COVID-19 and the structural evaluation of the affected organs. Reviewing and summarizing the application of MRI has significant clinical implications for COVID-19.</p><p><strong>Objective: </strong>The study aimed to analyze literature related to the application of MRI in COVID-19 using bibliometric tools, to explore the research status, hotspots, and developmental trends in this field, and to provide a reference for the application of MRI in the clinical diagnosis and evaluation of COVID-19.</p><p><strong>Methods: </strong>We used the Web of Science Core Collection database to search and collect relevant literature on the use of MRI in COVID-19. The authors, institutes, countries, journals, and keyword modules of the bibliometric analysis software CiteSpace and VOSviewer were used to analyze and plot the network map.</p><p><strong>Results: </strong>A total of 1506 relevant articles were shortlisted through the search; the earliest study was published in 2019, showing an overall upward trend every year. The research was mainly presented as published articles. Clinical neurology was found to be the primary discipline. The United States had the highest publication volume and influence in this field. Countries around the world cooperated more closely. The Cureus Journal of Medical Science was the main periodical to publish articles. Institutes, such as Harvard Medical School, Mayo Clinic, and Massachusetts General Hospital, have published a large number of papers. Some of the high-frequency keywords were \"COVID-19\", \"SARS-CoV-2\", \"magnetic resonance\", \"myocarditis\", and \"cardiac magnetic resonance imaging\". The keyword clustering study showed that the current research mainly focuses on five \"hot\" directions.</p><p><strong>Conclusion: </strong>There is a need to strengthen cross-teamwork and multidisciplinary collaboration in the future to completely explore the positive role of MRI in COVID-19 and to discover breakthroughs for the challenges in the clinical diagnosis and treatment of COVID-19.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139984439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Medical Image Fusion Based on Local Saliency Energy and Multi-scale Fractal Dimension.","authors":"Yaoyong Zhou, Xiaoliang Zhu, Panyun Zhou, Zhenwei Xu, Tianliang Liu, Wangjie Li, Renxian Ge","doi":"10.2174/0115734056273589231226052622","DOIUrl":"https://doi.org/10.2174/0115734056273589231226052622","url":null,"abstract":"<p><strong>Background: </strong>At present, there are some problems in multimodal medical image fusion, such as texture detail loss, leading to edge contour blurring and image energy loss, leading to contrast reduction.</p><p><strong>Objective: </strong>To solve these problems and obtain higher-quality fusion images, this study proposes an image fusion method based on local saliency energy and multi-scale fractal dimension.</p><p><strong>Methods: </strong>First, by using a non-subsampled contourlet transform, the medical image was divided into 4 layers of high-pass subbands and 1 layer of low-pass subband. Second, in order to fuse the high-pass subbands of layers 2 to 4, the fusion rules based on a multi-scale morphological gradient and an activity measure were used as external stimuli in pulse coupled neural network. Third, a fusion rule based on the improved multi-scale fractal dimension and new local saliency energy was proposed, respectively, for the low-pass subband and the 1st closest to the low-pass subband. Layerhigh pass sub-bands were fused. Lastly, the fused image was created by performing the inverse non-subsampled contourlet transform on the fused sub-bands.</p><p><strong>Results: </strong>On three multimodal medical image datasets, the proposed method was compared with 7 other fusion methods using 5 common objective evaluation metrics.</p><p><strong>Conclusion: </strong>Experiments showed that this method can protect the contrast and edge of fusion image well and has strong competitiveness in both subjective and objective evaluation.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139984459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fallopian Tube Leiomyoma Presenting as a Huge Abdominopelvic Cystic Mass: A Case Report and Literature Review.","authors":"Juan Wu, Xiaofeng Wang, Na Ye, Xueliang Yan, Xiangting Zeng, Fang Nie","doi":"10.2174/0115734056286949240130114710","DOIUrl":"https://doi.org/10.2174/0115734056286949240130114710","url":null,"abstract":"<p><strong>Introduction: </strong>Fallopian tube leiomyoma is an uncommon, benign gynecologic tumor that originates from the smooth muscle of the fallopian tube or vascular cells supplying the fallopian tube.</p><p><strong>Case presentation: </strong>In this study, we report a case of a patient with fallopian tube leiomyoma. What makes this instance even more unique is the association of the leiomyoma with cystic degeneration, manifesting as a large abdominopelvic cystic mass. CT scan suspected that the mass might be an ovarian cystadenoma. However, ultrasonography, a widely used diagnostic tool, effectively assisted the clinicians in confidently ruling out the possibility that the tumor was originating from the ovaries. Ultimately, the patient underwent exploratory laparoscopy and the pathologic diagnosis was fallopian tube leiomyoma with cystic degeneration. To our knowledge, no instance of a fallopian tube leiomyoma of this size with cystic degeneration has been reported. Thus, it is worth mentioning.</p><p><strong>Conclusion: </strong>In summary, fallopian tube leiomyomas are classified as uncommon benign gynecologic tumors, which pose challenges in clinical diagnosis. The combined use of multiple imaging modalities may be more helpful in the proper diagnosis of this disease entity.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139984444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"mSegResRF-SPECT: A Novel Joint Classification Model of Whole Body Bone Scan Images for Bone Metastasis Diagnosis.","authors":"Bangning Ji, Gang He, Jun Wen, Zhengguo Chen, Ling Zhao","doi":"10.2174/0115734056288472240129112028","DOIUrl":"https://doi.org/10.2174/0115734056288472240129112028","url":null,"abstract":"<p><strong>Background: </strong>Whole-body bone scanning is a nuclear medicine technique with high sensitivity used for the diagnosis of bone-related diseases [e.g., bone metastases] that can be obtained by positron emission tomography[PET] or single-photon emission computed tomography[SPECT] imaging, depending on the different radiopharmaceuticals used. In contrast to the high sensitivity of the bone scan, it has low specificity, which leads to misinterpretation, causing adverse effects of unwarranted intervention or interruption to timely treatment.</p><p><strong>Objective: </strong>To address this problem, this paper proposes a joint model called mSegResRF-SPECT, which accomplishes for the first time the task of classifying whole-body bone scan images on a public SPECT dataset [BS-80K] for the diagnosis of bone metastases.</p><p><strong>Methods: </strong>The mSegResRF-SPECT adopts a multi-bone region segmentation algorithm to segment the whole body image into 13 regions, ResNet34 as an extractor to extract the regional features, and a random forest algorithm as a classifier.</p><p><strong>Results: </strong>The experimental results of the proposed model show that the average accuracy, sensitivity, and F1 score of the model on the BS-80K dataset reached SOTA.</p><p><strong>Conclusion: </strong>The proposed method presents a promising solution for better bone scan classification methods.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139984465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}