Abstract: The present disclosure provides a cancer biomarker for a patient suffering from pleural effusion, a method of determining whether a patient suffering from pleural effusion has cancer, and a method of treating cancer in a patient suffering from pleural effusion. Disclosed herein also include a cancer biomarker for the detection of cancer with EGFR mutation, a method of determining whether a patient suffering from cancer has EGFR mutation, and a method of treating cancer in a patient with EGFR mutation.

Abstract: A method is proposed for identifying an anatomical structure within a spatial-temporal image (i.e. a series of frames captured as respective times). A current frame of spatial-temporal medical image is processed using information from one or more previous and/or subsequent temporal frames, to aid in the segmentation of an object or a region of interest (ROI) in a current frame. The invention is applicable to both two- and three-dimensional spatial-temporal images (i.e., 2D+time or 3D+time), and in particular to cardiac magnetic resonance (CMR images). An initialization process for this method segments the left ventricle (LV) in a CMR image by a fuzzy c-means (FCM) clustering algorithm which employs a circular shape function as part of the definition of the dissimilarity measure.

Abstract: A method is proposed for identifying an anatomical structure within a spatial-temporal image (i.e. a series of frames captured as respective times). A current frame of spatial-temporal medical image is processed using information from one or more previous and/or subsequent temporal frames, to aid in the segmentation of an object or a region of interest (ROI) in a current frame. The invention is applicable to both two- and three-dimensional spatial-temporal images (i.e., 2D+time or 3D+time), and in particular to cardiac magnetic resonance (CMR images). An initialisation process for this method segments the left ventricle (LV) in a CMR image by a fuzzy c-means (FCM) clustering algorithm which employs a circular shape function as part of the definition of the dissimilarity measure.

Abstract: A method and apparatus for determining coplanarity of three-dimensional features on a substrate comprises a support for an object to be inspected in an object plane, a light source for illuminating the object, a first image capturing device having a first sensor and a first tiltable lens, a second image capturing device having a second sensor and a second tiltable lens, and an image processor to determine the coplanarity. Each tiltable lens is movable from a first variable angle to a second variable angle, with respect to its sensor, so that the respective lens plane and its sensor plane substantially intersect at the object plane in accordance with the Scheimpflug principle and the respective image is in focus across the whole field of view and of uniform light intensity.

Abstract: A method and apparatus for determining coplanarity of three-dimensional features on a substrate comprises a support for an object to be inspected in an object plane, a light source for illuminating the object, a first image capturing device having a first sensor and a first tiltable lens, a second image capturing device having a second sensor and a second tiltable lens, and an image processor to determine the coplanarity. Each tiltable lens is movable from a first variable angle to a second variable angle, with respect to its sensor, so that the respective lens plane and its sensor plane substantially intersect at the object plane in accordance with the Scheimpflug principle and the respective image is in focus across the whole field of view and of uniform light intensity.