Accurate image segmentation plays a crucial role in computer vision and medical image analysis. In this study, we developed a novel uncertainty guided deep learning strategy (UGLS) to enhance the performance of an existing neural network (i.e., U-Net) in segmenting multiple objects of interest from images with varying modalities. In the developed UGLS, a boundary uncertainty map was introduced for each object based on its coarse segmentation (obtained by the U-Net) and then combined with input images for the fine segmentation of the objects. We validated the developed method by segmenting optic cup (OC) regions from color fundus images and left and right lung regions from Xray images. Experiments on public fundus and Xray image datasets showed that the developed method achieved a average Dice Score (DS) of 0.8791 and a sensitivity (SEN) of 0.8858 for the OC segmentation, and 0.9605, 0.9607, 0.9621, and 0.9668 for the left and right lung segmentation, respectively. Our method significantly improved the segmentation performance of the U-Net, making it comparable or superior to five sophisticated networks (i.e., AU-Net, BiO-Net, AS-Net, Swin-Unet, and TransUNet).

Semi-supervised segmentation plays an important role in computer vision and medical image analysis and can alleviate the burden of acquiring abundant expert-annotated images. In this paper, we developed a residual-driven semi-supervised segmentation method (termed RDMT) based on the classical mean teacher (MT) framework by introducing a novel model-level residual perturbation and an exponential Dice (eDice) loss. The introduced perturbation was integrated into the exponential moving average (EMA) scheme to enhance the performance of the MT, while the eDice loss was used to improve the detection sensitivity of a given network to object boundaries. We validated the developed method by applying it to segment 3D Left Atrium (LA) and 2D optic cup (OC) from the public LASC and REFUGE datasets based on the V-Net and U-Net, respectively. Extensive experiments demonstrated that the developed method achieved the average Dice score of 0.8776 and 0.7751, when trained on 10% and 20% labeled images, respectively for the LA and OC regions depicted on the LASC and REFUGE datasets. It significantly outperformed the MT and can compete with several existing semi-supervised segmentation methods (i.e., HCMT, UAMT, DTC and SASS).

The retina consists of various cell types arranged in eight cell layers and two membranes that originate from the neuroectodermal cells. In this study, the timing of differentiation and distribution of the cellular components and the layers of the rabbit retina are investigated using light and electron microscopy and immunohistochemical techniques. There were 32 rabbit embryos and 12 rabbits used. The rabbit retina begins its prenatal development on the 10th day of gestation in the form of optic cup. The process of neuro- and gliogenesis occurs in several stages: In the first stage, the ganglionic cells are differentiated at the 15th day. The second stage includes the differentiation of Muller, amacrine, and cone cells on the 23rd day. The differentiation of bipolar, horizontal, and rod cells and formation of the inner segments of the photoreceptors consider the late stage that occurs by the 27th and 30th day of gestation. On the first week of age postnatally, the outer segments of the photoreceptors are developed. S100 protein is expressed by the Muller cells and its processes that traverse the retina from the outer to the inner limiting membranes. Calretinin is intensely labeled within the amacrine and displaced amacrine cells. Ganglionic cells exhibited moderate immunoreactivity for calretinin confined to their cytoplasm and dendrites. In conclusion, all stages of neuro- and gliogenesis of the rabbit retina occur during the embryonic period. Then, the retina continues its development postnatally by formation of the photoreceptor outer segments and all layers of the retina become established. RESEARCH HIGHLIGHTS: The aim of this study is to investigate the morphogenesis of the rabbit retina during pre- and postnatal life. The primordia of the retina could be observed in the form of the optic cup. The ganglionic cells are the first cells to differentiate, while the photoreceptor cells are the last. S100 protein is expressed by the Muller cells and its processes. Calretinin is intensely labeled in the amacrine and displaced amacrine cells and moderately expressed in the cytoplasm and dendrites of ganglionic cells.

Proper estimation of the cup-to-disc ratio (C/D ratio) plays a significant role in ophthalmic examinations, and it is urgent to improve the efficiency of C/D ratio automatic measurement. Therefore, we propose a new method for measuring the C/D ratio of OCTs in normal subjects. Firstly, the end-to-end deep convolution network is used to segment and detect the inner limiting membrane (ILM) and the two Bruch\'s membrane opening (BMO) terminations. Then, we introduce an ellipse fitting technique to post-process the edge of the optic disc. Finally, the proposed method is evaluated on 41 normal subjects using the optic-disc-area scanning mode of three machines: BV1000, Topcon 3D OCT-1, and Nidek ARK-1. In addition, pairwise correlation analyses are carried out to compare the C/D ratio measurement method of BV1000 to existing commercial OCT machines as well as other state-of-the-art methods. The correlation coefficient between the C/D ratio calculated by BV1000 and the C/D ratio calculated by manual annotation is 0.84, which indicates that the proposed method has a strong correlation with the results of manual annotation by ophthalmologists. Moreover, in comparison between BV1000, Topcon and Nidek in practical screening among normal subjects, the proportion of the C/D ratio less than 0.6 calculated by BV1000 accounts for 96.34%, which is the closest to the clinical statistics among the three OCT machines. The above experimental results and analysis show that the proposed method performs well in cup and disc detection and C/D ratio measurement, and compared with the existing commercial OCT equipment, the C/D ratio measurement results are relatively close to reality, which has certain clinical application value.

Proper eye structure is essential for visual function: Multiple essential eye tissues must take shape and assemble into a precise three-dimensional configuration. Accordingly, alterations to eye structure can lead to pathological conditions of visual impairment. Changes in eye shape can also be adaptive over evolutionary time. Eye structure is first established during development with the formation of the optic cup, which contains the neural retina, retinal pigment epithelium, and lens. This crucial yet deceptively simple hemispherical structure lays the foundation for all later elaborations of the eye. Building on descriptions of the embryonic eye that started with hand drawings and micrographs, the field is beginning to identify mechanisms driving dynamic changes in three-dimensional cell and tissue shape. A combination of molecular genetics, imaging, and pharmacological approaches is defining connections among transcription factors, signaling pathways, and the intracellular machinery governing the emergence of this crucial structure.

Microphthalmia, anophthalmia, and coloboma (MAC) are congenital ocular malformations causing 25% of childhood blindness. The X-linked disorder Focal Dermal Hypoplasia (FDH) is frequently associated with MAC and results from mutations in Porcn, a membrane bound O-acyl transferase required for palmitoylation of Wnts to activate multiple Wnt-dependent pathways. Wnt/β-catenin signaling is suppressed in the anterior neural plate for initiation of eye formation and is subsequently required during differentiation of the retinal pigment epithelium (RPE). Non-canonical Wnts are critical for early eye formation in frog and zebrafish. However, it is unclear whether this also applies to mammals. We performed ubiquitous conditional inactivation of Porcn in mouse around the eye field stage. In Porcn CKO , optic vesicles (OV) arrest in growth and fail to form an optic cup. Ventral proliferation is significantly decreased in the mutant OV, with a concomitant increase in apoptotic cell death. While pan-ocular transcription factors such as PAX6, SIX3, LHX2, and PAX2 are present, indicative of maintenance of OV identity, regional expression of VSX2, MITF, OTX2, and NR2F2 is downregulated. Failure of RPE differentiation in Porcn CKO is consistent with downregulation of the Wnt/β-catenin effector LEF1, starting around 2.5 days after inactivation. This suggests that Porcn inactivation affects signaling later than a potential requirement for Wnts to promote eye field formation. Altogether, our data shows a novel requirement for Porcn in regulating growth and morphogenesis of the OV, likely by controlling proliferation and survival. In FDH patients with ocular manifestations, growth deficiency during early ocular morphogenesis may be the underlying cause for microphthalmia.

In vitro differentiation of human pluripotent stem cells (hPSCs) into specialized tissues and organs represents a powerful approach to gain insight into those cellular and molecular mechanisms regulating human development. Although normal embryonic eye development is a complex process, generation of ocular organoids and specific ocular tissues from pluripotent stem cells has provided invaluable insights into the formation of lineage-committed progenitor cell populations, signal transduction pathways, and self-organization principles. This review provides a comprehensive summary of recent advances in generation of adenohypophyseal, olfactory, and lens placodes, lens progenitor cells and three-dimensional (3D) primitive lenses, \"lentoid bodies\", and \"micro-lenses\". These cells are produced alone or \"community-grown\" with other ocular tissues. Lentoid bodies/micro-lenses generated from human patients carrying mutations in crystallin genes demonstrate proof-of-principle that these cells are suitable for mechanistic studies of cataractogenesis. Taken together, current and emerging advanced in vitro differentiation methods pave the road to understand molecular mechanisms of cataract formation caused by the entire spectrum of mutations in DNA-binding regulatory genes, such as PAX6, SOX2, FOXE3, MAF, PITX3, and HSF4, individual crystallins, and other genes such as BFSP1, BFSP2, EPHA2, GJA3, GJA8, LIM2, MIP, and TDRD7 represented in human cataract patients.

The development of the vertebrate eyes is a complex process starting from anterior-posterior and dorso-ventral patterning of the anterior neural tube, resulting in the formation of the eye field. Symmetrical separation of the eye field at the anterior neural plate is followed by two symmetrical evaginations to generate a pair of optic vesicles. Next, reciprocal invagination of the optic vesicles with surface ectoderm-derived lens placodes generates double-layered optic cups. The inner and outer layers of the optic cups develop into the neural retina and retinal pigment epithelium (RPE), respectively. In vitro produced retinal tissues, called retinal organoids, are formed from human pluripotent stem cells, mimicking major steps of retinal differentiation in vivo. This review article summarizes recent progress in our understanding of early eye development, focusing on the formation the eye field, optic vesicles, and early optic cups. Recent single-cell transcriptomic studies are integrated with classical in vivo genetic and functional studies to uncover a range of cellular mechanisms underlying early eye development. The functions of signal transduction pathways and lineage-specific DNA-binding transcription factors are dissected to explain cell-specific regulatory mechanisms underlying cell fate determination during early eye development. The functions of homeodomain (HD) transcription factors Otx2, Pax6, Lhx2, Six3 and Six6, which are required for early eye development, are discussed in detail. Comprehensive understanding of the mechanisms of early eye development provides insight into the molecular and cellular basis of developmental ocular anomalies, such as optic cup coloboma. Lastly, modeling human development and inherited retinal diseases using stem cell-derived retinal organoids generates opportunities to discover novel therapies for retinal diseases.

Automatic and accurate segmentation of optic disc (OD) and optic cup (OC) in fundus images is a fundamental task in computer-aided ocular pathologies diagnosis. The complex structures, such as blood vessels and macular region, and the existence of lesions in fundus images bring great challenges to the segmentation task. Recently, the convolutional neural network-based methods have exhibited its potential in fundus image analysis. In this paper, we propose a cascaded two-stage network architecture for robust and accurate OD and OC segmentation in fundus images. In the first stage, the U-Net like framework with an improved attention mechanism and focal loss is proposed to detect accurate and reliable OD location from the full-scale resolution fundus images. Based on the outputs of the first stage, a refined segmentation network in the second stage that integrates multi-task framework and adversarial learning is further designed for OD and OC segmentation separately. The multi-task framework is conducted to predict the OD and OC masks by simultaneously estimating contours and distance maps as auxiliary tasks, which can guarantee the smoothness and shape of object in segmentation predictions. The adversarial learning technique is introduced to encourage the segmentation network to produce an output that is consistent with the true labels in space and shape distribution. We evaluate the performance of our method using two public retinal fundus image datasets (RIM-ONE-r3 and REFUGE). Extensive ablation studies and comparison experiments with existing methods demonstrate that our approach can produce competitive performance compared with state-of-the-art methods.

Retinoic acid (RA) functions as an essential signal for development of the vertebrate eye by controlling the transcriptional regulatory activity of RA receptors (RARs). During eye development, the optic vesicles and later the retina generate RA as a metabolite of vitamin A (retinol). Retinol is first converted to retinaldehyde by retinol dehydrogenase 10 (RDH10) and then to RA by all three retinaldehyde dehydrogenases (ALDH1A1, ALDH1A2, and ALDH1A3). In early mouse embryos, RA diffuses to tissues throughout the optic placode, optic vesicle, and adjacent mesenchyme to stimulate folding of the optic vesicle to form the optic cup. RA later generated by the retina is needed for further morphogenesis of the optic cup and surrounding perioptic mesenchyme; loss of RA at this stage leads to microphthalmia and cornea plus eyelid defects. RA functions by binding to nuclear RARs at RA response elements (RAREs) that either activate or repress transcription of key genes. Binding of RA to RARs regulates recruitment of transcriptional coregulators such as nuclear receptor coactivator (NCOA) or nuclear receptor corepressor (NCOR), which in turn control binding of the generic coactivator p300 or the generic corepressor PRC2. No genes have been identified as direct targets of RA signaling during eye development, so future studies need to focus on identifying such genes and their RAREs. Studies designed to learn how RA normally controls eye development in vivo will provide basic knowledge valuable for determining how developmental eye defects occur and for improving strategies to treat eye defects.