Clinical patient characteristics.

<p>Clinical patient characteristics.</p

Figure 1

<p>Patient setup with the abdominal compression device (a) located in the upper abdomen region to limit the amount of respiration. (b) The data acquisition protocol for the PET/CT imaging of patients with abdominal compression immediately after conducting free-breathing imaging.</p

Summary of the quantitative results obtained using the conventional and abdominal compression methods.

<p>Summary of the quantitative results obtained using the conventional and abdominal compression methods.</p

Figure 2

<p>Coronal images of the (a) PET_FB/CT fusion image (left); PET_FB (right) and (b) PET_ab/CT_ab fusion image (left); and PET_ab (right) image for the selected patient, Patient 4. Misalignment around the tumor was observed in the PET_FB/CT fusion images (red arrow). (c) Vertical image profiles are drawn across the tumor in the PET_FB and PET_ab images.</p

Percentage difference (PD %) in tumor volume derived from PET images of the patients.

<p>Percentage difference (PD %) in tumor volume derived from PET images of the patients.</p

chovies

chovy nYears ago in Pigeon Inlet, the last thing a man'd do before he'd go to bed in the nights, was to make sure he had a good supply of chovies all ready to light his fire with next morning'. Grampa says makin' chovies was a skillful piece of business, and a man with a good sharp knife and some dry kindlin' could make 'em right bushy and fancy like... Another thing about chovies. Durin' the bad times, chovies was a great savin' on matches. A man wantin' to light his pipe'd just crack a limb off a chovy and hold it in the front grate of the stove...PRINTED ITEM G.M. StoryJAN 1978 JHJAN 1978Used I and SupUsed I1Used Ichoby, chopy, chuffy, shovy, MOP, MOP-HEAD, SHAVINGSChecked by Cathy Wiseman on Wed 24 Jun 201

Baseline characteristics of euthyroid, hyperthyroid and hypothyroid study subjects.

<p>* p<0.05, significant different from participants with euthyroid; ^a expressed as mean ± standard deviation.</p><p>Baseline characteristics of euthyroid, hyperthyroid and hypothyroid study subjects.</p

Radiomic features analysis in computed tomography images of lung nodule classification

<div><p>Purpose</p><p>Radiomics, which extract large amount of quantification image features from diagnostic medical images had been widely used for prognostication, treatment response prediction and cancer detection. The treatment options for lung nodules depend on their diagnosis, benign or malignant. Conventionally, lung nodule diagnosis is based on invasive biopsy. Recently, radiomics features, a non-invasive method based on clinical images, have shown high potential in lesion classification, treatment outcome prediction.</p><p>Methods</p><p>Lung nodule classification using radiomics based on Computed Tomography (CT) image data was investigated and a 4-feature signature was introduced for lung nodule classification. Retrospectively, 72 patients with 75 pulmonary nodules were collected. Radiomics feature extraction was performed on non-enhanced CT images with contours which were delineated by an experienced radiation oncologist.</p><p>Result</p><p>Among the 750 image features in each case, 76 features were found to have significant differences between benign and malignant lesions. A radiomics signature was composed of the best 4 features which included Laws_LSL_min, Laws_SLL_energy, Laws_SSL_skewness and Laws_EEL_uniformity. The accuracy using the signature in benign or malignant classification was 84% with the sensitivity of 92.85% and the specificity of 72.73%.</p><p>Conclusion</p><p>The classification signature based on radiomics features demonstrated very good accuracy and high potential in clinical application.</p></div

Selected feature.

<p>Selected feature.</p