Unsupervised Learning of Category-Specific Symmetric 3D Keypoints from Point Sets

Automatic discovery of category-specific 3D keypoints from a collection of objects of a category is a challenging problem. The difficulty is added when objects are represented by 3D point clouds, with variations in shape and semantic parts and unknown coordinate frames. We define keypoints to be category-specific, if they meaningfully represent objects’ shape and their correspondences can be simply established order-wise across all objects. This paper aims at learning such 3D keypoints, in an unsupervised manner, using a collection of misaligned 3D point clouds of objects from an unknown category. In order to do so, we model shapes defined by the keypoints, within a category, using the symmetric linear basis shapes without assuming the plane of symmetry to be known. The usage of symmetry prior leads us to learn stable keypoints suitable for higher misalignments. To the best of our knowledge, this is the first work on learning such keypoints directly from 3D point clouds for a general category. Using objects from four benchmark datasets, we demonstrate the quality of our learned keypoints by quantitative and qualitative evaluations. Our experiments also show that the keypoints discovered by our method are geometrically and semantically consistent

Induction of sodium iodide symporter gene and molecular characterisation of HNF3β/FoxA2, TTF-1 and C/EBPβ in thyroid carcinoma cells

Thyroid carcinoma cells often do not express thyroid-specific genes including sodium iodide symporter (NIS), thyroperoxidase (TPO), thyroglobulin (TG), and thyrotropin-stimulating hormone receptor (TSHR). Treatment of thyroid carcinoma cells (four papillary and two anaplastic cell lines) with histone deacetylase inhibitors (SAHA or VPA) modestly induced the expression of the NIS gene. The promoter regions of the thyroid-specific genes contained binding sites for hepatocyte nuclear factor 3 β (HNF3β)/forkhead box A2 (FoxA2), thyroid transcription factor 1 (TTF-1), and CCAAT/enhancer binding protein β (C/EBPβ). Quantitative reverse transcription-polymerase chain reaction (RT–PCR) showed decreased expression of HNF3β/FoxA2 and TTF-1 mRNA in papillary thyroid carcinoma cell lines, when compared with normal thyroid cells. Forced expression of these genes in papillary thyroid carcinoma cells inhibited their growth. Furthermore, the CpG island in the promoter region of HNF3β/FoxA2 was aberrantly methylated; and treatment with 5-aza-2-deoxycytidine (5-Az) induced its expression. Immunohistochemical staining showed that C/EBPβ was localised in the nucleus in normal thyroid cells but was detected in the cytoplasm in papillary thyroid carcinoma cells. Subcellular fractionation of papillary thyroid carcinoma cell lines also demonstrated high levels of expression of C/EBPβ in the cytoplasm, suggesting that a large proportion of C/EBPβ protein is inappropriately localised in the cytoplasm. In summary, these findings reveal novel abnormalities in thyroid carcinoma cell

Active stereo platform: online epipolar geometry update

This paper presents a novel method to update a variable epipolar geometry platform directly from the motor encoder based on mapping the motor encoder angle to the image space angle, avoiding the use of feature detection algorithms. First, an offline calibration is performed to establish a relationship between the image space and the hardware space. Second, a transformation matrix is generated using the results from this mapping. The transformation matrix uses the updated epipolar geometry of the platform to rectify the images for further processing. The system has an overall error in the projection of ± 5 pixels, which drops to ± 1.24 pixels when the verge angle increases beyond 10°. The platform used in this project has 3° of freedom to control the verge angle and the size of the baseline

ICAR: endoscopic skull‐base surgery

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