End-to-End Learnable Multi-Scale Feature Compression for VCM

The proliferation of deep learning-based machine vision applications has given rise to a new type of compression, so called video coding for machine (VCM). VCM differs from traditional video coding in that it is optimized for machine vision performance instead of human visual quality. In the feature compression track of MPEG-VCM, multi-scale features extracted from images are subject to compression. Recent feature compression works have demonstrated that the versatile video coding (VVC) standard-based approach can achieve a BD-rate reduction of up to 96% against MPEG-VCM feature anchor. However, it is still sub-optimal as VVC was not designed for extracted features but for natural images. Moreover, the high encoding complexity of VVC makes it difficult to design a lightweight encoder without sacrificing performance. To address these challenges, we propose a novel multi-scale feature compression method that enables both the end-to-end optimization on the extracted features and the design of lightweight encoders. The proposed model combines a learnable compressor with a multi-scale feature fusion network so that the redundancy in the multi-scale features is effectively removed. Instead of simply cascading the fusion network and the compression network, we integrate the fusion and encoding processes in an interleaved way. Our model first encodes a larger-scale feature to obtain a latent representation and then fuses the latent with a smaller-scale feature. This process is successively performed until the smallest-scale feature is fused and then the encoded latent at the final stage is entropy-coded for transmission. The results show that our model outperforms previous approaches by at least 52% BD-rate reduction and has $\times5$ to $\times27$ times less encoding time for object detection. It is noteworthy that our model can attain near-lossless task performance with only 0.002-0.003% of the uncompressed feature data size.Comment: Under peer review for IEEE TCSV

Modelling Surround-aware Contrast Sensitivity for HDR Displays

Despite advances in display technology, many existing applications rely on psychophysical datasets of human perception gathered using older, sometimes outdated displays. As a result, there exists the underlying assumption that such measurements can be carried over to the new viewing conditions of more modern technology. We have conducted a series of psychophysical experiments to explore contrast sensitivity using a state-of-the-art HDR display, taking into account not only the spatial frequency and luminance of the stimuli but also their surrounding luminance levels. From our data, we have derived a novel surroundaware contrast sensitivity function (CSF), which predicts human contrast sensitivity more accurately. We additionally provide a practical version that retains the benefits of our full model, while enabling easy backward compatibility and consistently producing good results across many existing applications that make use of CSF models. We show examples of effective HDR video compression using a transfer function derived from our CSF, tone-mapping, and improved accuracy in visual difference prediction

Long-term Results of Primary Total Knee Arthroplasty with and without Patellar Resurfacing

Among patients that underwent total knee arthroplasty from June, 1990 to January, 1999, 61 cases (44 patients) that could be followed for more than 10 years were included in this study. The patients were divided into a patellar retention group and a patellar resurfacing group, and were compared with regard to their clinical and radiological outcomes. In patients undergoing primary TKA, a selective patellar resurfacing protocol was used. The indications for patellar retention were a small patella, nearly normal articular cartilage, minimal preoperative patellofemoral pain, poor patellar bone quality, and young patient age. When patellar retention was performed, osteophytes of the patella were removed and marginal electrocauterization was carried out. There were 25 cases (20 patients) in the patellar retention group and 36 cases (29 patients) in the patellar resurfacing group. The mean follow-up period was 140.7 months in the patellar retention group and 149.0 months in the patellar resurfacing group. The selective patellar resurfacing with total knee arthroplasty had a favorable outcome;there were a significant difference noted between the 2 groups in the functional scores, which showed better outcomes in the patellar resurfacing group than in the patellar retention group

Quaternary structures of Vac8 differentially regulate the Cvt and PMN pathways.

Armadillo (ARM) repeat proteins constitute a large protein family with diverse and fundamental functions in all organisms, and armadillo repeat domains share high structural similarity. However, exactly how these structurally similar proteins can mediate diverse functions remains a long-standing question. Vac8 (vacuole related 8) is a multifunctional protein that plays pivotal roles in various autophagic pathways, including piecemeal microautophagy of the nucleus (PMN) and cytoplasm-to-vacuole targeting (Cvt) pathways in the budding yeast Saccharomyces cerevisiae. Vac8 comprises an H1 helix at the N terminus, followed by 12 armadillo repeats. Herein, we report the crystal structure of Vac8 bound to Atg13, a key component of autophagic machinery. The 70-angstrom extended loop of Atg13 binds to the ARM domain of Vac8 in an antiparallel manner. Structural, biochemical, and in vivo experiments demonstrated that the H1 helix of Vac8 intramolecularly associates with the first ARM and regulates its self-association, which is crucial for Cvt and PMN pathways. The structure of H1 helix-deleted Vac8 complexed with Atg13 reveals that Vac8[Delta 19-33]-Atg13 forms a heterotetramer and adopts an extended superhelical structure exclusively employed in the Cvt pathway. Most importantly, comparison of Vac8-Nvj1 and Vac8-Atg13 provides a molecular understanding of how a single ARM domain protein adopts different quaternary structures depending on its associated proteins to differentially regulate 2 closely related but distinct cellular pathways

MDCT and Gd-EOB-DTPA Enhanced MRI Findings of Adrenal Adenoma Arising from an Ectopic Adrenal Gland within the Liver: Radiologic-Pathologic Correlation

We report a case of an adenoma arising from an ectopic adrenal gland mimicking a hepatocellular carcinoma in a heavy alcohol abuser. A MDCT showed a 2.7 low-attenuating nodule in segment VII of the liver through all CT phases. Compared to a precontrast image, however, a subtle enhancement was noted on the arterial phase CT image. On T1 weighted in- and opposed-phase MR images, an abundant fat component within the lesion was seen. Dynamic contrast-enhanced MR images after administration of gadolinium ethoxybenzyl diethylenetriaminepentaacetic acid (Gd-EOB-DTPA) more clearly depicted hypervascularity and wash-out of the lesion on arterial and portal phases, respectively. On delayed hepatobiliary phase MR images, obtained 20 minutes after Gd-EOB-DTPA administration, subtle uptake or retention of the contrast agent by the lesion was suspected. A tumorectomy was performed and adrenal adenoma from an ectopic adrenal gland within the liver was confirmed

A case of congenital bilateral coronary-to-right ventricle fistula coexisting with variant angina

A coronary arteriovenous (AV) fistula consists of a communication between a coronary artery and a cardiac chamber, a great artery or the vena cava. It is the most common anomaly that can affect coronary perfusion. Yet bilateral involvement of a coronary fistula, constitutes an uncommon subgroup of coronary AV fistulas. We herein report on a case of bilateral coronary AV fistula that was coexistent with variant angina originating from the distal right ventricular branch of the right coronary artery and the distal septal branch of the left anterior descending artery, and the latter drained into the right ventricle