3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic Volumes

While deep convolutional neural networks (CNN) have been successfully applied for 2D image analysis, it is still challenging to apply them to 3D anisotropic volumes, especially when the within-slice resolution is much higher than the between-slice resolution and when the amount of 3D volumes is relatively small. On one hand, direct learning of CNN with 3D convolution kernels suffers from the lack of data and likely ends up with poor generalization; insufficient GPU memory limits the model size or representational power. On the other hand, applying 2D CNN with generalizable features to 2D slices ignores between-slice information. Coupling 2D network with LSTM to further handle the between-slice information is not optimal due to the difficulty in LSTM learning. To overcome the above challenges, we propose a 3D Anisotropic Hybrid Network (AH-Net) that transfers convolutional features learned from 2D images to 3D anisotropic volumes. Such a transfer inherits the desired strong generalization capability for within-slice information while naturally exploiting between-slice information for more effective modelling. The focal loss is further utilized for more effective end-to-end learning. We experiment with the proposed 3D AH-Net on two different medical image analysis tasks, namely lesion detection from a Digital Breast Tomosynthesis volume, and liver and liver tumor segmentation from a Computed Tomography volume and obtain the state-of-the-art results

Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography: Comparison With 101 Radiologists.

BACKGROUND: Artificial intelligence (AI) systems performing at radiologist-like levels in the evaluation of digital mammography (DM) would improve breast cancer screening accuracy and efficiency. We aimed to compare the stand-alone performance of an AI system to that of radiologists in detecting breast cancer in DM. METHODS: Nine multi-reader, multi-case study datasets previously used for different research purposes in seven countries were collected. Each dataset consisted of DM exams acquired with systems from four different vendors, multiple radiologists' assessments per exam, and ground truth verified by histopathological analysis or follow-up, yielding a total of 2652 exams (653 malignant) and interpretations by 101 radiologists (28 296 independent interpretations). An AI system analyzed these exams yielding a level of suspicion of cancer present between 1 and 10. The detection performance between the radiologists and the AI system was compared using a noninferiority null hypothesis at a margin of 0.05. RESULTS: The performance of the AI system was statistically noninferior to that of the average of the 101 radiologists. The AI system had a 0.840 (95% confidence interval [CI] = 0.820 to 0.860) area under the ROC curve and the average of the radiologists was 0.814 (95% CI = 0.787 to 0.841) (difference 95% CI = -0.003 to 0.055). The AI system had an AUC higher than 61.4% of the radiologists. CONCLUSIONS: The evaluated AI system achieved a cancer detection accuracy comparable to an average breast radiologist in this retrospective setting. Although promising, the performance and impact of such a system in a screening setting needs further investigation

Volumetric breast density measurement for personalized screening : Accuracy, reproducibility, and agreement with visual assessment

Assessment of breast density at the point of mammographic examination could lead to optimized breast cancer screening pathways. The onsite breast density information may offer guidance when to recommend supplemental imaging for women in a screening program. In this work, performance evaluation of a new software (Insight BD, Siemens Healthcare GmbH) for fast onsite quantification of volumetric breast density is presented. Accuracy of volumetric measurement is evaluated using breast tissue equivalent phantom experiments. Reproducibility of measurement results is analyzed using 8150 4-view mammography exams. Furthermore, agreement between breast density categories computed by the software with those determined visually by radiologists is examined. The results of the performance evaluation demonstrate that the software delivers accurate and reproducible measurements that agree well with the visual assessment of breast density by radiologists

A human observer study for evaluation and optimization of reconstruction methods in breast tomosynthesis using clinical cases

In breast tomosynthesis1 (BT) a number of 2D projection images are acquired from different angles along a limited arc. The imaged breast volume is reconstructed from the projection images, providing 3D information. The purpose of the study was to investigate and optimize different reconstruction methods for BT in terms of image quality using human observers viewing clinical cases. Sixty-six cases with suspected masses and calcifications were collected from 55 patients. Four different reconstructions of each image set were evaluated by four observers (two experienced radiologists, two experienced medical physicists): filtered back projection (FBP), iterative adapted FBP (iFBP) and two ML-convex iterative algorithm (MLCI) reconstructions (8 and 10 iterations) that differed in noise level and contrast of clinical details. Representation of masses and microcalcifications was evaluated. The structures were rated according to the overall appearance in a rank-order study. The differently reconstructed images of the same structure were displayed side by side in random order. The observers were forced to rank the order of the different reconstructed images and their proportions at each rank were scored. The results suggest that even though the FBP contains most noise its reconstructions are considered best overall, followed by iFBP, which contains least noise. In both FBP and iFBP methods the sharp borders and mass speculations were better represented than in iterative reconstructions while out-of-plane artifacts were better suppressed in the latter. However, in clinical practice the differences between the reconstructions may be considered negligible

Volumetric breast density measurement for personalized screening : Accuracy, reproducibility, consistency, and agreement with visual assessment

Assessment of breast density at the point of mammographic examination could lead to optimized breast cancer screening pathways. The onsite breast density information may offer guidance of when to recommend supplemental imaging for women in a screening program. A software application (Insight BD, Siemens Healthcare GmbH) for fast onsite quantification of volumetric breast density is evaluated. The accuracy of the method is assessed using breast tissue equivalent phantom experiments resulting in a mean absolute error of 3.84%. Reproducibility of measurement results is analyzed using 8427 exams in total, comparing for each exam (if available) the densities determined from left and right views, from cranio-caudal and medio-lateral oblique views, from full-field digital mammograms (FFDM) and digital breast tomosynthesis (DBT) data and from two subsequent exams of the same breast. Pearson correlation coefficients of 0.937, 0.926, 0.950, and 0.995 are obtained. Consistency of the results is demonstrated by evaluating the dependency of the breast density on women's age. Furthermore, the agreement between breast density categories computed by the software with those determined visually by 32 radiologists is shown by an overall percentage agreement of 69.5% for FFDM and by 64.6% for DBT data. These results demonstrate that the software delivers accurate, reproducible, and consistent measurements that agree well with the visual assessment of breast density by radiologists

Focus-detector arrangement of an X-ray apparatus for generating projective or tomographic phase contrast recordings

A focus-detector arrangement of an X-ray apparatus is disclosed for generating projective or tomographic phase contrast recordings of an observed region of a subject. In at least one embodiment, the arrangement includes a radiation source which emits a coherent or quasi-coherent X-radiation and irradiates the subject, a phase grating which is arranged behind the subject in the beam path of the radiation source and generates an interference pattern of the X-radiation in a predetermined energy range, and an analysis-detector system which detects at least the interference pattern generated by the phase grating in respect of its phase shift with position resolution. Further, the beam path of the X-radiation used diverges in at least one plane between the focus and the detector

X-ray optical transmission grating of a focus-detector arrangement of an X-ray apparatus for generating projective or tomographic phase contrast recordings of a subject

An X-ray optical transmission grating of a focus-detector arrangement of an X-ray apparatus is disclosed, for generating projective or tomographic phase contrast recordings of a subject. In at least one embodiment, the grating includes a multiplicity of grating bars and grating gaps arranged periodically on at least one surface of at least one wafer, wherein the X-ray optical transmission grating includes at least two sub-gratings arranged in direct succession in the beam direction

Focus Detector Arrangement For Generating Phase-Contrast X-Ray Images and Method for this

A bundled electron beam (BEB) (14) is controlled regarding its excursion in its direction by two pairs of plate electrodes (17.1,17.2;18.1,18.2) that operate vertically to each other. The BEB can use appropriate control of these plate electrodes to scan an anode (16) like scanning a TV picture line by line with a desirable gap and, as a result, can generate desired X-rays. Independent claims are also included for the following: (1) An X-ray system for generating projective phase-contrast exposures; (2) A method for generating projective or tomographic X-ray phase-contrast exposures of an object under examination with the help of a focus-detector system

Focus-detector arrangement for generating projective or tomographic phase contrast recordings with X-ray optical gratings

A focus-detector arrangement of an X-ray apparatus is disclosed for generating projective or tomographic phase contrast recordings with a phase grating. According to at least one embodiment of the invention, in the gaps between its bars, the phase grating includes a filler material whose linear attenuation coefficient in the relevant energy range is greater than that of the bars. The height of the filler material in the gaps is dimensioned on the one hand so that the X-radiation with the energy used for measuring the phase shift generates a phase shift in the X-radiation such that, after the phase grating, the rays which pass through the bars are phase shifted by one half wavelength relative to the rays which pass through the gaps with the filler material. Further, the height of the filler material in the gaps on the other hand is dimensioned so that the attenuation of the X-radiation, at least in relation to the energy used for measuring the phase shift, is the same when passing through the bars and when passing through the filler material