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The mass and concentration of hemoglobin per erythrocyte are important hematological parameters. Measuring these parameters from intact erythrocytes requires the value of specific refraction-index increment (RII) of oxygenated hemoglobin, which diverges in the literature. Refractive indices of hemoglobin solutions are measured directly by digital holographic microscopy on a microfluidic channel filled with hemoglobin solutions prepared by hemolysis of fresh human erythrocytes and refractive-index standards sequentially. Hemoglobin extracted from thalassemic patients shows 3–4% higher RII than that from healthy volunteers, but the difference is not significant in comparison to inter-subject variations within each group. The quantified RIIs are applied to quantify mean corpuscular hemoglobin mass of blood from 37 human subjects, and results are in accord with standard clinical test results.

Significance: Label-free quantitative phase imaging is a promising technique for the automatic detection of abnormal red blood cells (RBCs) in real time. Although deep-learning techniques can accurately detect abnormal RBCs from quantitative phase images efficiently, their applications in diagnostic testing are limited by the lack of transparency. More interpretable results such as morphological and biochemical characteristics of individual RBCs are highly desirable. Aim: An end-to-end deep-learning model was developed to efficiently discriminate thalassemic RBCs (tRBCs) from healthy RBCs (hRBCs) in quantitative phase images and segment RBCs for single-cell characterization. Approach: Two-dimensional quantitative phase images of hRBCs and tRBCs were acquired using digital holographic microscopy. A mask region-based convolutional neural network (Mask R-CNN) model was trained to discriminate tRBCs and segment individual RBCs. Characterization of tRBCs was achieved utilizing SHapley Additive exPlanation analysis and canonical correlation analysis on automatically segmented RBC phase images. Results: The implemented model achieved 97.8% accuracy in detecting tRBCs. Phase-shift statistics showed the highest influence on the correct classification of tRBCs. Associations between the phase-shift features and three-dimensional morphological features were revealed. Conclusions: The implemented Mask R-CNN model accurately identified tRBCs and segmented RBCs to provide single-RBC characterization, which has the potential to aid clinical decision-making.

PURPOSE: Segmentation of the left ventricle (LV) in cardiac CT (CCT) images is difficult due to the intensity heterogeneity arising from accumulation of contrast agent in papillary muscle and trabeculae carneae. In this study, we demonstrated the random walks method for LV segmentation in CCT through cardiac phases. METHODS: 63 CCT data sets from 7 patients with 9 cardiac phases were included in this study. All cardiac CT examinations were performed with GE 64-detector CT scanner with ECG gating. In each patient, 60–80 ml iohexol was injected at a flow rate of 5 ml/sec followed by 60 ml normal saline solution. Random walks (RW) based on probability of labels was used for LV segmentation. The LV delineations generated by the experienced physician (MD), conventional image-based method (IB), and RW were compared. RESULTS: In general the contours segment the LV closely by RW and MD, but the discrepancies in papillary muscle and trabeculae carneae were observed while using the IB method. CONCLUSION: We showed the RW method potentially improved LV segmentation as compared to the volume by conventional IB method. In this study, we demonstrated the clinical feasibility of LV volume segmentation using random walks algorithm.

Ventricular hemodynamics plays an important role in assessing cardiac function in clinical practice. The aim of this study was to determine the ventricular hemodynamics based on contrast movement in the left ventricle (LV) between the phases in a cardiac cycle recorded using an electrocardiography (ECG) with cardiac computed tomography (CT) and optical flow method. Cardiac CT data were acquired at 120 kV and 280 mA with a 350 ms gantry rotation, which covered one cardiac cycle, on the 640-slice CT scanner with ECG for a selected patient without heart disease. Ventricular hemodynamics (mm/phase) were calculated using the optical flow method based on contrast changes with ECG phases in anterior-posterior, lateral and superior-inferior directions. Local hemodynamic information of the LV with color coating was presented. The visualization of the functional information made the hemodynamic observation easy.

Background and purpose: Computational fluid dynamics method (CFDM) and optical flow method (OFM) effec- tively provide the hemodynamic information based on the digital subtraction angiogram (DSA). However, the quantitative analysis in comparison of CFDM and OFM is still absent. The goal of this study is to apply CFDM and OFM in quantitative analysis of stenting treatment. Material and method: A left carotid stenosis patient underwent stenting of percutaneous transluminal angioplasty was ana- lyzed as an example. CFDM and OFM for hemodynamic analysis on digital subtraction angiography before and after stenting treatment were presented. Results: Improvement gains of blood flow velocities on left internal carotid artery after stenting treament for different initial conditions on the common carotid artery were 1.91∼2.13, 1.62∼2.09, and 0.69 by CFDM with Newtonian and non-Newtonian fluids and OFM, respectively. With the CFDM analysis, the flow mapping by OFM using time resolved DSA data on the fl yt o estimate hemodynamic significance of a cervical carotid stenosis was explained. Conclusion: Quantificative blood flow estimations by CFDM and OFM to evaluate the treatment outcomes to patient with carotid stenosis are practical. Both methods are able to provide quantitative information of blood flow for stenting treatment. It is advantagious to use both methods in treatment evaluation.

Image registration is often a required and a time-consuming step in blood flow analysis of large microscopic video sequences in vivo. In order to obtain stable images for blood flow analysis, frame-to-frame image matching as a preprocessing step is a solution to the problem of movement during image acquisition. In this paper, microscopic system analysis without fluorescent labelling is performed to provide precise and continuous quantitative data of blood flow rate in individual microvessels of nude mice. The performance properties of several matching metrics are evaluated through simulated image registrations. An automatic image registration programme based on Powell's optimisation search method with low calculation redundancy was implemented. The matching method by variance of ratio is computationally efficient and improves the registration robustness and accuracy in practical application of microcirculation registration. The presented registration method shows acceptable results in close requisition to analyse red blood cell velocities, confirming the scientific potential of the system in blood flow analysis.

Complete blood count is the most common test to detect anemia, but it is unable to obtain the abnormal shape of erythrocytes, which highly correlates with the hematologic function. Tomographic diffractive microscopy (TDM) is an emerging technique capable of quantifying three-dimensional (3-D) refractive index (RI) distributions of erythrocytes without labeling. TDM was used to characterize optical and morphological properties of 172 erythrocytes from healthy volunteers and 419 erythrocytes from thalassemic patients. To efficiently extract and analyze the properties of erythrocytes, we developed an adaptive region-growing method for automatically delineating erythrocytes from 3-D RI maps. The thalassemic erythrocytes not only contained lower hemoglobin content but also showed doughnut shape and significantly lower volume, surface area, effective radius, and average thickness. A multi-indices prediction model achieved perfect accuracy of diagnosing thalassemia using four features, including the optical volume, surface-area-to-volume ratio, sphericity index, and surface area. The results demonstrate the ability of TDM to provide quantitative, hematologic measurements and to assess morphological features of erythrocytes to distinguish healthy and thalassemic erythrocytes.

Objectives Respiration-induced motion in the liver causes potential errors on the measurement of contrast medium in abdominal artery from multiphase hepatic CT scans. In this study, we investigated the use of hepatic CT images to quantitatively estimate the abdominal artery motion due to respiration by optical flow method. Materials and Methods A total of 132 consecutive patients were included in our patient cohort. We apply the optical flow method to compute the motion of the abdominal artery due to respiration. Results The minimum and maximum displacements of the abdominal artery motion were 0.02 and 30.87 mm by manual delineation, 0.03 and 40.75 mm calculated by optical flow method, respectively. Both high consistency and correlation between the present method and the physicians’ manual delineations were acquired with the regression equation of movement, y = 0.81x+0.25, r = 0.95, p

OBJECTIVE We analyzed intracranial regional blood flows using an optical flow method (OFM) and digital subtraction angiography in patients with internal carotid artery (ICA) stenosis. We also retrospectively explored the correlation between the patients' diagnoses and the severity of the ICA stenoses. MATERIALS AND METHODS OFM, an image-processing algorithm to estimate motion, was applied to determine the mean velocity V(mean) in the vessels. A group of 40 patients without vascular anomalies acted as the control group. The patients were classified as having either moderate stenosis ( 80%, n=23). RESULTS The V(mean) of the ICAs was significantly lower in the stenotic group compared with the control group (p< 0.01). The V(mean) of the ICAs was inversely correlated with the severity of the stenosis (p< 0.05). The receiver operating characteristic curve of the V(mean) in an AP view showed substantial discriminatory power, with an optimal cutoff value of 3.48 pixels/frame for the detection of patients with carotid stenosis. The sensitivity and specificity were 84% and 50%, respectively. On a lateral view, the best cutoff for the V(mean) was 4.01 pixels/frame, and the sensitivity and specificity were 92% and 43%, respectively. CONCLUSIONS Digital subtraction angiography combined with the OFM is a feasible parametric method for intracranial blood flow measurements in patients with moderate to severe carotid stenosis.

Objective. We applied optical flow method (OFM) to quantify relative velocities of blood flow using digital subtraction angiography (DSA) in the vascular analysis of hepatocellular carcinoma (HCC) patients who underwent transarterial chemoembolization (TACE) treatment.Methods. A total of 40 HCC patients treated by TACE were analyzed in this study. DSA imaging with a 12-inch field of view, 1024 × 1024 pixels and 4 frames/second was acquired. OFM developed for motion estimation is applied for blood flow estimation. Two acrylic phantoms were built to validate the method.Results. The relationship between the OFM and Doppler measurements was found linear withR2=0.99for both straight and curved tube phantoms. Quantitative blood flow distribution images of the portal vein region were presented. After TACE, the minimum, maximum and mean velocities in the portal vein all decreased (P<0.05). Additionally, the velocity in the portal vein is significantly lower with a higher Child-Pugh score (P<0.01).Conclusions. The present technique provides add-on quantitative information of flows to DSA and the hemodynamic analysis in relative quantifications of blood flow in portal vein of hepatocellular carcinoma patients using DSA.

The progression of epithelial precancers into cancer is accompanied by changes of tissue and cellular structures in the epithelium. Correlations between the structural changes and scattering coefficients of esophageal epithelia were investigated using quantitative phase images and the scattering-phase theorem. An ex vivo study of 14 patients demonstrated that the average scattering coefficient of precancerous epithelia was 37.8% higher than that of normal epithelia from the same patient. The scattering coefficients were highly correlated with morphological features including the cell density and the nuclear-to-cytoplasmic ratio. A high interpatient variability in scattering coefficients was observed and suggests identifying precancerous lesions based on the relative change in scattering coefficients.