Classification of Sleep Apnea through Sub-band Energy of Abdominal Effort Signal Using Wavelets + Neural Networks

Detection and classification of sleep apnea syndrome (SAS) is a critical problem. In this study an efficient method for classification sleep apnea through sub-band energy of abdominal effort using a particularly designed hybrid classifier as Wavelets + Neural Network is proposed. The Abdominal respiration signals were separated into spectral sub-band energy components with multi-resolution Discrete Wavelet Transform (DWT). The energy content of these spectral components was applied to the input of the artificial neural network (ANN). The ANN was configured to give three outputs dedicated to SAS cases; obstructive sleep apnea (OSA), central sleep apnea (CSA) and mixed sleep apnea (MSA). Through the network, satisfactory results that rewarding 85.62% mean accuracy in classifying SAS were obtained.     

A Wavelet-Based Mammographic Image Denoising and Enhancement with Homomorphic Filtering

Breast cancer continues to be a significant public health problem in the world. The diagnosing mammography method is the most effective technology for early detection of the breast cancer. However, in some cases, it is difficult for radiologists to detect the typical diagnostic signs, such as masses and microcalcifications on the mammograms. This paper describes a new method for mammographic image enhancement and denoising based on wavelet transform and homomorphic filtering. The mammograms are acquired from the Faculty of Medicine of the University of Akdeniz and the University of Istanbul in Turkey. Firstly wavelet transform of the mammograms is obtained and the approximation coefficients are filtered by homomorphic filter. Then the detail coefficients of the wavelet associated with noise and edges are modeled by Gaussian and Laplacian variables, respectively. The considered coefficients are compressed and enhanced using these variables with a shrinkage function. Finally using a proposed adaptive thresholding the fine details of the mammograms are retained and the noise is suppressed. The preliminary results of our work indicate that this method provides much more visibility for the suspicious regions.     

乳腺微钙化对良、恶性乳腺病变的诊断价值

目的探讨乳腺微小钙化灶的特征与乳腺良、恶性病变的关系。方法观察分析115例乳腺钼铑双靶X线片中微小钙化灶的特征,并和临床病理检查结果进行对照研究。结果钙化灶的形态、数目、密集度、钙化灶区范围以及钙化灶是否合并肿块与乳腺病变的性质密切相关。结论钙化灶的分布特征与乳腺病变的性质密切相关,从乳腺钼靶片上可粗略的预测病变的性质,从而为临床内分泌治疗、手术治疗、判断疾病的预后提供依据。     

Classification of breast microcalcifications: radiological-pathological correlation

Background Microcalcifications play a very important role in detection of breast cancer, especially early stage breast cancer. However, ambiguity still exists in understanding the relationship between radiological and pathological characteristics of microcalcifications. The definitive indication of a biopsy has not been established. The purpose of this study is to evaluate the relationship of classification of breast microcalcifications using full-field digital mammography to the pathological characteristics. Methods For all the women an open biopsy had been conducted. One hundred and three mammographs showing clustered microcalcifications from 98 consecutive patients were reviewed along with their pathological records. To investigate the value of each criterion for the detection of cancer, univariate and multivariate analyses were performed on the entire sample and then on morphological subgroups.Results Pathological examination showed 67 malignant lesions (65.05%) and 36 benign lesions (34.95%). In the univariate analysis, four radiological variables were significant: morphological type (P=0.001), complicated by a mass (P=0.002), number of microcalcifications per cluster (P=0.02) and linear or triangular distribution of clusters (P=0.009). In the multivariate analysis, two criteria remained significant: morphological type (P<0.001) and complicated by a mass (P=0.001). The percentage of malignancy was 37.0%, 60.0%, 78.8%, and 88.9%, respectively, for type 2 (regularly punctiform), type 3 (dusty), type 4 (irregularly punctiform) and type 5 (vermicular) microcalcifications (Le Gal’s classification). The malignancy was 78.6% for microcalcifications complicated by a mass and 48.9% without a mass. The difference was significant (P<0.05). The relationship between morphological types of microcalcifications and the pathological characteristics was also studied. In subgroups, type 3 (dusty) microcalcifications complicated by a mass (P=0.001) or with the number of microcalcifications more than 10 (P=0.024); and type 2 (regularly punctiform) with a diameter of the area over 20 mm (P=0.024) or complicated by a mass (P=0.025) were statistically significant as criteria for malignant tumour. Conclusions Most cases of microcalcifications of type 4 or 5; type 3 complicated by a mass or with the number of microcalcifications more than 10; type 2 complicated by a mass or with a diameter of the area over 20 mm; are indicative of cancer. Open biopsy is recommended to acquire definitive pathological diagnosis for these cases. For the remainder of the morphological types, stereotaxic biopsy or followup should be considered.     

A New Watermarking System Based on Discrete Cosine Transform (DCT) in Color Biometric Images

This paper recommend a biometric color images hiding approach An Watermarking System based on Discrete Cosine Transform (DCT), which is used to protect the security and integrity of transmitted biometric color images. Watermarking is a very important hiding information (audio, video, color image, gray image) technique. It is commonly used on digital objects together with the developing technology in the last few years. One of the common methods used for hiding information on image files is DCT method which used in the frequency domain. In this study, DCT methods in order to embed watermark data into face images, without corrupting their features.     

Clinical experience of the first digital mammographic unit in Australia in its first year of use

In April 2004, Melbourne's Peter MacCallum Cancer Centre, Australia's only stand-alone dedicated cancer hospital, became the first Australian site to offer digital mammography (DM). In the first year of DM operation, 1208 mammograms were performed on 1157 women; 17 new cases of invasive carcinoma and six new cases of ductal carcinoma-in-situ (DCIS) were detected; and 30 hook-wire needle localisations were conducted in 29 patients. We developed a unit policy to manage indeterminate microcalcifications newly demonstrated on DM that were not previously detected by conventional screen-film mammography (CM): those believed to have malignant morphology were recommended for biopsy, and those without were recommended for 6-month DM follow-up to confirm microcalcification stability. DM detected 56 new stand-alone microcalcifications (18 suspicious and 38 indeterminate). Tissue diagnosis of 12 suspicious microcalcifications yielded four cases of DCIS and one of atypical ductal hyperplasia. Of the indeterminate microcalcifications, 35 have demonstrated stability at DM follow-up to date, over a mean period of 23.6 months. From our experience, we believe DM's superior demonstration ability uncovered microcalcifications previously undetected by CM, rather than microcalcification progression. We suggest that routine review with DM, rather than biopsy, is appropriate management when new indeterminate microcalcifications without malignant characteristics are identified by DM.     

Medical Image Retrieval Using Vector Quantization and Fuzzy S-tree

The aim of the article is to present a novel method for fuzzy medical image retrieval (FMIR) using vector quantization (VQ) with fuzzy signatures in conjunction with fuzzy S-trees. In past times, a task of similar pictures searching was not based on searching for similar content (e.g. shapes, colour) of the pictures but on the picture name. There exist some methods for the same purpose, but there is still some space for development of more efficient methods. The proposed image retrieval system is used for finding similar images, in our case in the medical area – in mammography, in addition to the creation of the list of similar images – cases. The created list is used for assessing the nature of the finding – whether the medical finding is malignant or benign. The suggested method is compared to the method using Normalized Compression Distance (NCD) instead of fuzzy signatures and fuzzy S-tree. The method with NCD is useful for the creation of the list of similar cases for malignancy assessment, but it is not able to capture the area of interest in the image. The proposed method is going to be added to the complex decision support system to help to determine appropriate healthcare according to the experiences of similar, previous cases.     

MR增强扫描与钼钯检查对导管原位癌的诊断价值

目的 比较MR增强扫描和钼钯对乳腺导管原位癌的诊断价值.方法 收集2010 ～ 2011年经手术证实为导管原位癌的33位病人(平均年龄60岁,平均病灶大小15 mm)作为研究对象,在术前常规进行MR增强扫描和钼钯检查.结果 在经病理证实为导管原位癌33例病人中,MR增强扫描诊断出29例患导管原位癌,其敏感性是87.9％.其中有4例导管原位癌被诊断为良性.而33例病人中钼钯检查诊断21例患导管原位癌(其中包括没有被MR检出的病人),其敏感性是63.6％,其它12例都是由MR增强扫描诊断出.结论 钼钯和MR增强扫描都能检出没有钙化的隐匿性导管原位癌,但是MR增强扫描在诊断伴有钙化的小的病灶时需要经钼钯证实.     

乳腺单纯簇状钙化灶数字化钼铑双靶X线摄影的影像表现及临床价值

目的：应用数字化钼铑双靶摄影观察乳腺内局灶性单纯簇状微钙化灶的影像表现,探讨其诊断及治疗价值。方法：使用GE Senographe2000D全数字钼铑双靶乳腺摄影机,全自动曝光条件,常规头尾位、侧斜位或加摄侧位对乳腺1.0cm2内单纯簇状钙化灶进行定位诊断后行手术治疗。对部分较小簇状钙化灶术后病灶组织再摄片确定钙化灶切除是否完整。对其中3例微小钙化灶术后摄片同时针刺定位以助病理切片。结果：21例25个钙化灶中,簇状微细钙化19例23个病灶;分支状钙化灶1例1个病灶,粗细不均钙化灶1例1个病灶。经手术、病理证实为浸润型乳腺癌7例9个病灶（占36%）,早期浸润型乳癌12例14个病灶（56%）;良性病变2例2个病灶（8%）。结论：数字化钼铑双靶乳腺摄影可提高早期乳腺癌及微小乳腺癌的检出率。乳腺术前术后摄片可以辅助手术切除病灶、病理取材,提高乳腺疾病的临床诊断治疗水平。     

计算机乳腺摄影诊断乳腺疾病的价值

目的　探讨计算机乳腺摄影对乳腺疾病的诊断价值 ,提高早期乳腺癌的诊断水平。方法　应用高频钼靶乳腺机和CR系统进行计算机乳腺摄影检查 ,回顾性分析经手术和活检病理证实的 2 82 7例乳腺疾病的结果 ,研究早期乳腺癌的X线表现。结果　 2 82 7例检出乳腺癌 683例 ,乳腺良性病变 2 144例。早期乳腺癌的主要X线征象有 :小结节、群集的微小钙化簇、局部结构紊乱和小斑片状浸润。结论　计算机乳腺摄影是乳腺疾病较可靠的影像学检查方法 ,对早期乳腺癌的诊断很有价值     

Internet of Things with Maximal Overlap Discrete Wavelet Transform for Remote Health Monitoring of Abnormal ECG Signals

In this paper, MODWT is used to decompose the Electrocardiography (ECG) signals and to identify the changes of R waves in the noisy input ECG signal. The MODWT is used to handle the arbitrary changes in the input signal. The R wave’s detctected by the proposed framework is used by the doctors and careholders to take necessary action for the patients. MATLAB simulink model is used to develop the simulation model for the MODWT method. The performance of the MODWT based remote health monitoring system method is comparatively analyzed with other ECG monitoring approaches such as Haar Wavelet Transformation (HWT) and Discrete Wavelet Transform (DWT). Sensitivity, specificity, and Receiver Operating Characteristic (ROC) curve are calculated to evaluate the proposed Internet of Things with MODWT based ECG monitoring system. We have used MIT-BIH Arrythmia Database to perform the experiments.     

磁共振弥散加权成像的纹理特征鉴别良恶性单纯微钙化型乳腺隐匿性病灶的价值

目的: 探索使用磁共振弥散加权成像（DWI）的纹理特征鉴别良恶性单纯微钙化型乳腺隐匿性病灶的价值。方法: 回顾性分析2012年10月至2015年12月于浙江省肿瘤医院进行乳腺X射线金属丝三维定位的61例（38例恶性肿瘤、23例良性病变）单纯微钙化型乳腺隐匿性病灶患者的DWI影像。对每个感兴趣区域提取6个直方图特征和16个灰度共生矩阵纹理特征。利用随机森林算法进行特征选择并构建分类器,使用留一法进行交叉验证。采用ROC曲线评价分类器的性能。结果: 筛选获得的性能最佳的特征组合共包含6个特征,分别为直方图中的均值、方差、偏度、熵,以及灰度共生矩阵的0°方向对比度、45°方向相关性,其中,直方图中的均值、方差、偏度和熵在良性病变与恶性肿瘤组间差异有统计学意义（均P < 0.05）。由上述特征构建的分类器鉴别诊断单纯微钙化型乳腺隐匿性病灶良性病变与恶性肿瘤的AUC达到0.76,诊断准确率、敏感度、特异度分别为77.05%、84.21%、65.21%。结论: DWI的纹理特征分析能在一定程度上提高良恶性单纯微钙化型乳腺隐匿性病灶诊断的准确性,直方图中的均值、方差、偏度和熵是极具潜力的影像学标志物。     

Luminance Sticker Based Facial Expression Recognition Using Discrete Wavelet Transform for Physically Disabled Persons

Developing tools to assist physically disabled and immobilized people through facial expression is a challenging area of research and has attracted many researchers recently. In this paper, luminance stickers based facial expression recognition is proposed. Recognition of facial expression is carried out by employing Discrete Wavelet Transform (DWT) as a feature extraction method. Different wavelet families with their different orders (db1 to db20, Coif1 to Coif 5 and Sym2 to Sym8) are utilized to investigate their performance in recognizing facial expression and to evaluate their computational time. Standard deviation is computed for the coefficients of first level of wavelet decomposition for every order of wavelet family. This standard deviation is used to form a set of feature vectors for classification. In this study, conventional validation and cross validation are performed to evaluate the efficiency of the suggested feature vectors. Three different classifiers namely Artificial Neural Network (ANN), k-Nearest Neighborhood (kNN) and Linear Discriminant Analysis (LDA) are used to classify a set of eight facial expressions. The experimental results demonstrate that the proposed method gives very promising classification accuracies.     

乳腺良恶性病变中微钙化钼靶X线征象分析

目的:探讨微钙化钼靶X线征象在乳腺良、恶性病变中的诊断及鉴别诊断的价值,以提高诊断准确性。方法:收集经术后病理证实术前均行X线摄影伴有微钙化的乳腺癌病人35例及乳腺良性病变37例,回顾性分析比较其钙化数目、密度、密集度、形态及分布特点。结果:乳腺良恶性病变微钙化在密度、数目、密集度、形态及分布5个指标方面差异有统计学意义（P<0.05～P<0.01）。乳腺癌中表现为低密度为主的微钙化比例高于乳腺良性病变组（P<0.05）。乳腺癌钙化数目≥20所占比例明显高于乳腺良性病变组（P<0.05）。乳腺癌微钙化密集度≥10/cm2所占比例明显高于乳腺良性病变组（P<0.01）。形态上良性组粗颗粒样钙化所占比例高,乳腺癌组仅出现1例,乳腺癌组中细沙样、线形分支样、蠕虫样及混合型钙化出现率高（P<0.01）。分布上弥漫状分布仅见于良性组,线状及段状分布乳腺癌组所占比例较高（P<0.01）结论:微钙化灶的数目、密度、密集度、形态及分布特征与乳腺良、恶性病变有一定关系,其钼靶X线征象可对乳腺良、恶性病变作出初步判断。     

Exploration of computerized image processing in underexposed and overexposed X-rays of bones and joints

Objective: To study the effective computerized image processing of underexposed and overexposed X-rays of bones and joints. Methods: Ninety-nine conventional X-ray images (82 were overexposed and 17 were underexposed), scanned by an UMAX Astra 4000U Scanner, were converted into digital images on the basis of their analog images. A computerized imaging processing program consisting of five functional modules such as Contrast Stretch, Fast Flourier Transform (FFT), Image Smoothing Modules, Inverse Fast Flourier Transform (IFFT) and Nonlinear Transform performed image contrast stretch and smoothing. Three senior doctors from hospital image sections made their evaluation of all the proeessed images. Restilts: Of 82 overexposed films, 71 met the clinical requirements after image processing, and 11 were unable to be applied to clinical diagnosis, accounting for 87% and 13% respectively. Of the other 17 underexposed X-ray images, 11 met the clinical requirements while 6 were not, making a percentage of 64 and 35. Conclusion: Image contrast stretch and smoothing processing are significantly effective on conventional X-ray images which were inappropriately exposed, and can avoid more X-ray radiation caused by handling of radiological photograph again. This method can decrease hospital cost and provide acute and effective X-ray examinations for the treatment and cure for critical patients.     

乳腺癌微小钙化灶与C-erbB-2、ER、PR表达的相关性

目的 探讨微小钙化灶的临床价值,评估乳腺癌人类上皮生长因子受体-2(C-erbB-2)、雌激素受体(ER)及孕激素受体(PR)异常表达与微小钙化的相关性.方法 回顾性分析经X线检查、手术病理证实的91例乳腺癌患者,评估乳腺微小钙化灶诊断乳腺癌的准确率,按照ACR创立并推荐的BI-RADS,将X线所见钙化征象分为微小钙化组,中间型钙化组,无钙化组进行描述,并与C-erbB-2、ER及PR表达进行对照,分析其相关性.结果 乳腺癌微小钙化灶与C-erbB-2的异常表达有显著相关性(P＜0.05),而与ER、PR表达无明显相关性.结论 乳腺癌微小钙化是其特征性表现,与C-erbB-2表达有一定关联性,可粗略预测C-erbB-2表达情况,并为判断肿瘤生物学行为及患者预后提供一定参考价值.     

Effective Management of Medical Information Through A Novel Blind Watermarking Technique

Medical Data Management (MDM) domain consists of various issues of medical information like authentication, security, privacy, retrieval and storage etc. Medical Image Watermarking (MIW) techniques have recently emerged as a leading technology to solve the problems associated with MDM. This paper proposes a blind, Contourlet Transform (CNT) based MIW scheme, robust to high JPEG and JPEG2000 compression and simultaneously capable of addressing a range of MDM issues like medical information security, content authentication, safe archiving and controlled access retrieval etc. It also provides a way for effective data communication along with automated medical personnel teaching. The original medical image is first decomposed by CNT. The Low pass subband is used to embed the watermark in such a way that enables the proposed method to extract the embedded watermark in a blind manner. Inverse CNT is then applied to get the watermarked image. Extensive experiments were carried out and the performance of the proposed scheme is evaluated through both subjective and quantitative measures. The experimental results and comparisons, confirm the effectiveness and efficiency of the proposed technique in the MDM paradigm.     

数字化乳腺双靶X线机诊断乳腺疾病1600例分析

目的:探讨采用美国GE公司产钼铑双靶X线机摄片系统对乳腺癌的诊断价值.方法:通过数字化后处理方法,对1 600例乳腺疾病患者钼钝双靶X线摄片结果进行分析.结果:具备更高质量的乳腺图像,提高了乳腺疾病的诊断正确率,而且能够发现原有的单钯X线机所不易检出的疾病,如微小乳腺癌及微小钙化等,大大地提高了乳腺癌的早期检出率,而且其对人体辐射剂量减少,更具人性化,适合临床应用.     

乳腺隐匿性病灶定位穿刺切除技术及应用

目的：探讨临床触诊阴性而乳腺影像检查阳性的隐匿性乳腺病变行定位穿刺留置导丝引导手术切除活检的技术操作及应用价值。方法：临床触诊阴性，而乳腺X线或CT摄片显示成簇的细小钙化、模糊小结节及局部结构紊乱等微小病灶，通过穿刺留置导丝于可疑的病灶区，然后手术切取活体组织行病理学检查。结呆：38例45处病灶均一次性定位成功，未发生出血、导丝脱出等并发症。X线钼靶定位穿刺25处病灶，其中小结节边界模糊致密灶3处，成簇或较集中的微小钙化灶21处，局部结构紊乱1处。CT定位穿刺20处病灶，其中小结节边界模糊致密灶15处，微小钙化灶4处，局部结构紊乱1处。病理结果：恶性病变3例3处病灶，癌前病变4例6处，良性病变31例36处。结论：立体定位穿刺留置导丝引导手术活检术对乳腺隐匿性病变定位准确，不仅能使手术精确切除乳腺微小病灶，又能有效减少腺体损伤，是早期发现乳腺癌的有效途径。     

钼靶检查对隐匿性乳腺癌的诊断价值

目的探讨钼靶检查在隐匿性乳腺癌中的X线表现及诊断价值。方法回顾性分析34例手术病理证实的隐匿性乳腺癌的钼靶X线表现。结果X线表现孤立模糊小结节影5例,簇状微小钙化18例,乳腺结构紊乱4例,单纯腋下淋巴结肿大4例,血管增多、增粗、迂曲3例。病理诊断浸润性导管癌20例,导管原位癌8例,小叶原位癌4例,浸润性小叶癌2例。结论通过对隐匿性乳腺癌的钼靶X线征象分析,说明钼靶检查在隐匿性乳腺癌的诊断方面具有较高的诊断价值。